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Digital & Data Career Advice - Why is salary important
Seems a bit obvious doesn’t it? But it’s not JUST about salary. Our consultants work closely with job seekers to understand what motivates them, we then match them with the perfect company and team based on job requirements, career aspirations, and cultural fit. Within this video, Scandi recruiters James Allen, Luke Parkinson, Johnnie Savva, and Danny Arnold discuss how to find your worth, and what else you should be looking for. Watch the video to find out more!
Digital & Data Career Advice - Why Asking About Salary Is Essential
When it comes to asking certain questions in an interview it can be daunting. However, some questions are more important than others. When applying for a job, asking about your salary is essential. Should you ask the interviewer direct? Or discuss it with your consultant? Scandi recruiters James Allen, Luke Parkinson, Johnnie Savva, and Danny Arnold discuss this topic in our latest video. If you have any other questions, don’t hesitate to get in touch.
Digital & Data Career Advice - Top Tips For Creating A Good CV
Are you looking for a new job? Has it been a while since you last moved roles? Are your CV writing skills a bit rusty? We have great news. In this video James Allen, Luke Parkinson, Johnnie Savva, and Danny Arnold talk about their top tips for those who are looking to create a good CV. If you have any questions, don’t hesitate to ask!
Digital & Data Career Advice - One Page CV.... Yes or No?
One-page CV.... Yes or No? Is it more important to condense your CV to make it more digestible and to stand out from the crowd? If you're up against 50/60 applicants, with no one representing you, then maybe. But, if you're working with a recruiter, it's actually their job to make you stand out.... Could a one-page CV make you come across as lazy? Maybe you should have 2 versions of a CV.... Watch the video and join the discussion.
Digital & Data Career Advice - What should be on your CV?
What should you include in your CV for a digital role? Will this differ for a Data position? How much information should you include about yourself, your hobbies, and your interests? What are should have more prevalence? Experience? Tech stack? Education? What about a CV for Data roles? Should you focus more on project work? How your function fit into a wider team? Check out our video to find out more....
Digital & Data Career Advice - How we can help with your interview process
When looking for a new job, the interview process can sometimes be daunting. At Darwin, we want to make sure that you have the best experience possible. In our latest career advice video, Scandi recruiters James Allen, Luke Parkinson, Johnnie Savva, and Danny Arnold talk about how we can help you throughout the interview process, making it easier and smoother both for you and the interviewer. Watch this video to find out more!
Our New Swiss Market Update with an exclusive interview with EF Education
DOWNLOAD HERE: https://bit.ly/3kEhqkL We’ve just launched a brand new edition of our SWISS MARKET UPDATE. This edition is bigger than ever, with 5 brand new data points per tech specialism including: - Gender split - Average tenure - Top employers - Fastest growing skills - Education levels This is all in addition to the salary benchmarks and time to hire data that you come to expect from a Darwin Market Update. I’m even more excited about this edition as it features an interview with Patrick Kammermann from EF Education First. In this interview, Patrick discusses the fantastic culture at EF Education; how they successfully hire and nurture diverse teams, and how they maintain a start-up, entrepreneurial outlook as a global organisation.
Congratulations Derk Rijntjes
APSCo Deutschland – The German arm of the Association of Professional Staffing Companies (APSCo) – has announced the latest individuals elected to its Representative Committee and our very own Derk Rijntjes has been selected. Congratulations Derk, your years of dedication to the sector, breadth of industry experience, an in-depth understanding of IT recruitment will make you an invaluable member of the committee. Check out the full article here: https://bit.ly/2PZLvzR
**SPECIAL EPISODE**: Creating and Nurturing the RIGHT Start-Up Culture
**SPECIAL PODCAST EPISODE** **LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/6NvLabiLpASevKXBxL3i4I LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/creating-and-nurturing-the-right-start-up-culture/id1529453970?i=1000511224799 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3e3ROfH “If the emissions gap is not closed by 2030 it is extremely unlikely that the 2 degrees temperature goal can still be reached.” In this special podcast episode, Eden Whitcomb chats to Lubomila Jordanova Co-founder & CEO of PlanA.Earth and Co-Founder of Greentech alliance, about how they’re using tech to do their bit to save the planet. But, healthy relationships are equally as important. No business is successful without them, and PlanA.Earth shares some great examples of how to nurture these relationships. In this special episode, Lubomila calls upon her vast experience to offer advice on the following: How to maintain relationships in a larger business How to create a culture in a business How to deal with setbacks How has COVID affected a business? Are you looking for a new front-end job in Berlin? Are you looking to hire in Berlin? Contact Eden now for an informal chat, he'll be happy to give you all the information you need.
Tech specialists at the forefront of hiring at Pexip
Nicklas Jensen, is a Software Engineer at Pexip, the Scandinavian video conferencing powerhouse. Pexip has made the interesting (and, to us, joyous) decision to give the responsibility of hiring someone who is at the forefront of business technology. Brad Wilkins, Scandinavian Team Manager at Darwin speaks to Nicklas about what he looks for when hiring new team members. Are you looking for a new Frontend job in Norway? Are you looking to hire in Norway? Contact Bradley now for an informal chat, he'll be happy to give you all the information you need. Bradley: This year has been tough for everyone. What advice would you give, as a Software Engineer who is also in charge of hiring, to anyone who’s considering changing jobs at the moment? Nicklas: This is so this is funny because I actually get this question a lot now that I’ve informed my friends and family that I’m looking after recruitment. Especially in these times. I think my main answer to that is to put some energy into it. I know that can be difficult when you have to apply for 50 jobs or even hundreds now because it’s so competitive, but put some energy into it, go that extra mile to make your CV look a little great. Go that extra mile. Right. Go that extra mile. Make sure that the application is personalized to the business that you’re applying to. Try not to send a generic application to all. For us, when we get an application from someone who doesn’t have a lot of experience but who took the time to write their application to what they think our values are, that’s an instant interview. It’s it really matters a lot that you take the time to (short and concisely, we’re not talking essays here) describe why you think that the company is a fit for you.nIt’s also a matter of reflection, right? When you sit down and write that personalized application, what feeling does that leave you with? Are you writing it because you feel like you have to because it’s an open position, but, actually, you’re just dragging yourself through it? Maybe you should look for a different position to apply for. Right? And I speak from experience myself. When I had to find a job coming from Spain to Norway, I could have just done what a lot of people do, which is just to fire off a hundred applications. But, rather, I tried to find companies that would truly add value to my career. Actually, it was you, Brad, that contacted me and found me a job at FedEx, at the time. I only said that because you presented it in a way that I related to. I wouldn’t have said yes to anything if I didn’t relate to. That energy comes through in an application, the feeling like you could actually belong in that company, even if it’s just text on paper, it comes through in the way you write. It comes through in the amount of detail and effort you put into it. It might take longer. Yes. But it also will get you that interview or it will definitely increase your chances of getting to the interview stage. Brad: I agree. I think we’ve all had those applications where you can tell it’s mass-generated, or it only four lines with a name and a generic overview of what they’re looking for. But, as you said, I’d be more motivated to look at an application if there were reasoning and passion behind it. We see this when we’re posting our adverts. I often get the same person applying to five or ten jobs that I’m advertising with a generic application. I think, if you put that extra mile in and showcase why your skills, expertise, and passion suits that one particular role and the value that you alone can add, I think that’s definitely a powerful bit of advice.
Building a startup in the retail industry and the effects of the pandemic
Omnium AS is the first pure order processing system in Norway; a cloud solution that allows their customers to deliver an omnichannel retail experience. Johnnie Savva, .Net specialist here at Darwin, interviewed Omnium’s CEO, Petter Balstad, about how the Pandemic has affected the retail industry and how he’s had to quickly adapt his business to ride the wave. Are you looking for a new .NET job in Norway? Are you looking to hire in Norway? Contact Johnnie now for an informal chat, he'll be happy to give you all the information you need. Johnnie: Let’s go back to September 2017, when you’ve just you’ve just decided to take the leap to becoming a business owner, what challenges did you face? What advice would you give to anyone who is thinking about leaving their current job to go and start their own business in the tech industry? Petter: It’s a lot more difficult than you think it would be because you’re having the final word and what you’re saying will directly impact your company. People are always talking about founding a company or starting a startup, and how it is so much work. And yes, it is, from time to time. You work crazy hours, especially the tech guys. But, at the same time, I would say it’s it’s challenging intellectually as well because it’s difficult. There’s a lot of rules and regulations that you need to understand and a responsibility that you don’t really think about when you first thought of starting a company; when you’re just focusing on your idea and how you can bring that to life and then sell it to customers. But it’s so much more than that; when you start hiring people you feel a huge responsibility for those people who need to be paid every month, have their own family and so on. But, putting that aside, it’s crazy fun and so fulfilling and rewarding. So I wouldn’t be without it. It’s been a great ride. And, I haven’t really thought about it but, this month. It’s been three years! Johnnie: So, really, you’re almost coming out of that start-up phase and now Omnium are looking to take that next step in the coming months and years, and progressing. So you’d say that the stereotypes are correct in a way? Sleeping in the office, long hours as well but some enjoyable things too; when you start winning business? Does that sound right? Petter: Yes, definitely. We’re crawling out of our shell right now. So we’re ready to hire more people and to scale up both internationally and in terms of the number of employees we have; we’re scaling the entire company. So, hopefully, the worst, crazy days are behind us. Johnnie: On the subject of the challenges of setting up the business, those three years ago, would you that the experience you gained throughout your career helped you? Or would you say, in preparation to starting Omnium you had to take some business management courses or had to speak to other startup founders about their experiences? Or, was it a natural progression for you? Petter: Well, we basically jumped straight in to see; can we do this? Can we do it better than many others? What will we learn while doing it? So, no courses, no schooling, doing it the hard way, succeeding sometimes, failing many times, but then just trying not to make the same mistakes again. It’s really interesting you say that because I speak to a lot of startup founders and many give off the impression that it is indeed ‘plain sailing’. Some founders won’t admit to their mistakes and others will. Johnnie: Would you say that, actually, that’s the biggest learning curve that you guys have experienced? Making those mistakes, be it around technical development or business practices and then learning from them, that’s been the biggest pathway to success? Petter: Yeah, probably. Just the mindset of being okay with making mistakes takes you one step closer to doing it right. So, it’s totally OK to do something wrong or make a mistake, because that also takes us forward. You learn to like the mistakes, in a way. That was definitely a big learning curve. Yeah, definitely. Johnnie: You can lean on that, can’t you? Once you understand that you can learn from it and use it to your advantage, then it becomes a benefit. Petter: Definitely. I think the people that assume that starting a company and getting it right will be ‘plain sailing’, I think they’re in for a wake-up call.
Season One Darwin RechDoTech Podcast
Season 1 of the Darwin RecDoTech Podcast has come to an end. In the New Year, we'll be kicking off Season 2 with more fantastic, tech-focussed, recruitment-led discussions for you. Let's take a look back at our fantastic first season, featuring Amazon, Google, SNAP inc, AON, Yelp, DataRobot, and many more: Ep 1: Women in AI with Dr. Nancy Ranxing Li, Ph.D. Spotify: https://open.spotify.com/episode/0QegK7NvjwkIh6edvv1bBW Apple Music: https://podcasts.apple.com/us/podcast/women-in-ai-with-dr-nancy-ranxing-li-ph-d/id1529453970?i=1000489298144 Google Podcasts: https://bit.ly/3rO93VG Ep 2: Implementing Lean Start-Up Methodology with Lorenzo Di Nobili, Founder of Grazie Spotify: https://open.spotify.com/episode/1woIRYmuulHWjdOddtQH1H Apple Music: https://podcasts.apple.com/us/podcast/implementing-lean-start-up-methodology-lorenzo-di-nobili/id1529453970?i=1000489868015 Google Podcasts: https://bit.ly/3sVSAjJ Ep 3: Creating an Unbiased Working Environment with Sarah Noovari @Snap Inc. Spotify: https://open.spotify.com/episode/0VBQNTCFVe97F6ejTTJxL6 Apple Music: https://podcasts.apple.com/us/podcast/creating-unbiased-working-environment-sarah-noovari/id1529453970?i=1000490461353 Google Podcasts: https://bit.ly/3wGxXKG Ep 4: Building a Personal Brand in Tech with Eric Weber @Yelp Spotify: https://open.spotify.com/episode/3vH3mSLBzL5KMdqGCWDNGR Apple Music: https://podcasts.apple.com/us/podcast/building-a-personal-brand-in-tech-with-eric-weber-yelp/id1529453970?i=1000491312949 Google Podcasts: https://bit.ly/3fHT9db Ep 5: Making Smarter Tech Career Decisions with Ben Taylor @ DataRobot Spotify: https://open.spotify.com/episode/5T7XZnYcT9MwpHK0BWu9aR Apple Music: https://podcasts.apple.com/us/podcast/making-smarter-tech-career-decisions-ben-taylor-datarobot/id1529453970?i=1000492126909 Google Podcasts: https://bit.ly/3fIINcP Ep 6: Mothers in Tech with Gayle@ Amazon, Brandee @ Appetize and Kate @ DATAcated Spotify: https://open.spotify.com/episode/1COAyr05QZtNj69XkMAEhZ Apple Music: https://podcasts.apple.com/us/podcast/mothers-in-tech-gayle-amazon-brandee-appetize-kate/id1529453970?i=1000493102628 Google Podcasts: https://bit.ly/3cTbfqD Ep 7: Hire & Build a Data Science Team with Graham Morehead @ AON Spotify: https://open.spotify.com/episode/4WOOvrNfBffCqXkaPTDKXn Apple Music: https://podcasts.apple.com/us/podcast/hire-build-a-data-science-team-with-graham-morehead-aon/id1529453970?i=1000494009701 Google Podcasts: https://bit.ly/2PvOKiV Ep 8: Data Science - A woman's perspective with Maria Ovchinnikova @ Portchain Spotify: https://open.spotify.com/episode/5ch7ZYuDj7ANOVbfMBCbnk Apple Music: https://podcasts.apple.com/us/podcast/data-science-womans-perspective-maria-ovchinnikova/id1529453970?i=1000494859846 Google Podcasts: https://bit.ly/3fM9GMY Ep 9: Leading Elite NLP Teams with Imed Zitouni @ Google Spotify: https://open.spotify.com/episode/0Lc2R8YRNDZ7o9udghNZ2o Apple Music: https://podcasts.apple.com/us/podcast/leading-elite-nlp-teams-with-imed-zitouni-google/id1529453970?i=1000495419814 Google Podcasts: https://bit.ly/31MPXEO Ep 10: From Dream to Reality - Build a Data Startup with Jacopo Tagliabue @ Coveo Spotify: https://open.spotify.com/episode/0UDR83ytgPsLzrrJnhlg68 Apple Music: https://podcasts.apple.com/us/podcast/from-dream-to-reality-build-data-startup-jacopo-tagliabue/id1529453970?i=1000496361842 Google Podcasts: https://bit.ly/3rWRLWm Ep 11: The CTO Onboarding Process with Kevin Goldsmith @ Anaconda Spotify: https://open.spotify.com/episode/2zaTQ5J18HUirZpTuVrpsI Apple Music: https://podcasts.apple.com/us/podcast/the-cto-onboarding-process-with-kevin-goldsmith-anaconda/id1529453970?i=1000497454718 Google Podcasts: https://bit.ly/3fKswUQ Ep 12: Mental Health in Tech - The Invisible Enemy with Will Falkowski Spotify: https://open.spotify.com/episode/0yfBjfuD2JOrE63prgJRzi Apple Music: https://podcasts.apple.com/us/podcast/mental-health-in-tech-invisible-enemy-will-falkowski/id1529453970?i=1000498853235 Google Podcasts: https://bit.ly/3mmhqqg Ep 13: The 'Sibling Rivalry' between Internal and External Recruiters with Amy Miller Spotify: https://open.spotify.com/episode/4GeKN9AwCT6d2XKcEeozop Apple Music: https://podcasts.apple.com/us/podcast/sibling-rivalry-between-internal-external-recruiters/id1529453970?i=1000501762029 Google Podcasts: https://bit.ly/3fKNymr
RecDoTech Podcast Episode 13: The Rivalry between Internal & External Recruiters
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/4GeKN9AwCT6d2XKcEeozop LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/sibling-rivalry-between-internal-external-recruiters/id1529453970?i=1000501762029 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3pQwAoU REC DO TECH PODCAST SEASON 1 - FINAL EPISODE THE RIVALRY BETWEEN INTERNAL & EXTERNAL RECRUITERS Why is there so much animosity between internal and external recruiters? "An external recruiter isn't trying to take the job of an internal recruiter. We'd actually be far more successful if we worked together. Is it about taking credit?" Lewis Adams-Dunstan chats to Amy Miller, Senior In-house Tech recruiter in this open, honest and funny discussion. Here's a snippet but you can listen to the full episode on Spotify or Apple Podcasts. Are you looking for a new Data science job in the US? Are you looking to hire in the US? Contact Lewis now for an informal chat, he will be happy to give you all the information you need.
Relocating to Hamburg Featuring Picalike GMBH
Founded in 2010, Picalike is a leading SaaS provider for visual technology, empowering e-commerce. The product portfolio, fueled by artificial intelligence, boosts the performance of online shops and marketplaces. Adam Slade chats to Sebastian Kielmann, Picalike’s CEO, about why Hamburg is the perfect location for his business, or for anyone looking for a tech job in Germany. Adam Slade: When it came to choosing, not only what the product is, but where the product is going to be based, you founded it in Hamburg. What was the decision behind choosing Hamburg as the location in which you’d grow and build the business from scratch? Sebastian Kielmann: So why Hamburg? Firstly, I lived in Hamburg. Secondly, because our biggest customer is in Hamburg, which is the OTTO Group, and then 15 or 16 of our customers are out of the OTTO Group, and are settled here in Hamburg. I also like the culture of Hamburg. It’s more family-friendly than other startup cities, but that’s my own private opinion. Adam Slade: When I’m speaking to developers and engineers, outside of Germany, who are potentially looking at moving into the country, Berlin always seems to be the default location for a those looking for their next developer job or software engineer job. It’s, of course, a very well-known start-up hub and has an international culture, but Hamburg is heading in that direction and we’re seeing more success stories come out of Hamburg as well. Sebastian Kielmann: : I guess, first of all, when all the start-up growth in Berlin began, prices were very low for an apartment. But they have exploded over the last year! So, Berlin isn’t a cheap city any more compared to Hamburg, Munich, Frankfurt or Cologne. Berlin has a very different culture compared to Hamburg. People are totally different there. And it’s also huge compared to Hamburg. So in Hamburg, you have everything that you have in Berlin, but the distances between one thing and another are shorter. Hamburg is very, very green. So you have a lot of parks, you have a lot of green areas, and it’s not a long journey to get to the water. So I like to go kitesurfing and if you like to walk on the beach, Hamburg is very, very close to the sea when compared to Berlin. But there is one overarching difference between Hamburg and Berlin; they have a different startup mentality. If you’re in Berlin, you don’t have to speak German. If you’re in Berlin, you don’t have to fit in with the German culture; you’re in Berlin. If you’re in Hamburg, you would slowly start to get more acclimatized to the Northern German culture and, up to a certain point, you would have to gain more language experience. So if you’re looking to move to Germany, just want to work there and don’t want to have anything to do with the culture of the country, don’t want to learn the strange language they speak there, then you’re well suited to go to Berlin. If you want to go to Germany because you like the culture and want to become a part of the community there, then you’re more suited to Hamburg. You’ll learn that people here are very friendly; if they tell you something, they really mean it. If you like this type of culture, want to learn the language, integrate yourself and if you want to stay for a long time and build on the ‘family’ surroundings, then Hamburg is the city for you. Adam Slade: Do you think, if someone was seriously considering moving to Hamburg, they would need to learn German to make that a long-term base of operations? Or, if you're looking for a great developer job in Germany, could an English speaker survive in the city? Sebastien Kielmann: An English speaker would survive in the city. But you would feel better if, over a certain period of time, let’s say, over the next five years or so, started learning German, at least to a certain point, because it would make your life easier and could integrate better. So, I’m Brazilian and I have friends in Berlin who came from Brazil and they live in like a ‘Brazilian bubble’ in Germany because they mostly speak Portuguese and sometimes English. They meet their Brazilian friends, they go to restaurants together. There are even parties where only people from Brazil attend; So you’re in another country, living the culture of your own country, which is OK, it’s fine. But if you’re in Hamburg, you’ll experience more of a variety and you’ll be slowly introduced more and more into the Hamburg culture and less tempted to stick to what you’re already used to. If you're looking for a new job in Hamburg, or you're planning to hire tech talent in Hamburg, reach out to Adam Slade.
Why Hamburg was the location for us, featuring Loxonet GmbH
Loxonet GmbH is a Hamburg based software company, founded in 2018 by Benedikt Weitz. Benedikt built his ‘intelligent administration’ business to support organisations with 50 to 1000 employees, by centralising all areas of Their communication and administration onto one central platform. Here Benedikt tells Adam Slade the reasons behind starting his business in Hamburg. Adam Slade: When creating any business, you need to choose the base of operations, correct? You’ve experienced building businesses all over Germany but, this time, you’ve ended up in beautiful Hamburg. Why Hamburg this time? Benedikt: Well, there are professional reasons and then there are personal reasons. So, if I look back at my life, I was very gifted and had the chance to travel a lot. I was in the army for two years and I studied to become a Lieutenant in Bavaria. I was originally from Cologne (which can be well heard when I drink my first beer) and meanwhile, I was also in Berlin. So indeed, I’ve really covered the West, the South, the middle and the East of Germany. In my latest station, before Hamburg, I was in Berlin and decided to make my mind up about where I really wanted to be. I was looking for a great combination of industry, roughness, nearness to the sea, but as well as that, a beautiful city. I visited friends in Hamburg multiple times and felt that it’s the place for me. I very much appreciate the quality of living and working in Hamburg. Hamburg is very well connected to the rest of Germany. So, looking at the structure of Hamburg, there are many, many offices here. There are many family businesses as well. There’s a lot of logistics and trading and not that great orientation to ‘service only’ as found in Berlin. That made it more attractive to me. In Hamburg we’re dedicated to producing great companies and to the transport industry. Adam Slade: Do you think that, with the incredibly fast rate that companies have been founded in Berlin, it’s almost intimidating to try and build a business in a location where there are so many others doing the same thing? Benedikt: It would be so easy to give a short reply but that’s a tough question and it’s very difficult to be precise. Of course, the financial infrastructure for startups in Berlin is better. If you look at the infrastructure of VCs etc. However, there are more startups located there, so, you could get lost in the great variety of them. The reason why I’d like to advocate Hamburg as a startup location; in my point of view, it has a very special ‘Made in Germany’ stamp. Hamburg’s values are hard-working and traditional but, at the same time, it’s a very international and qualitative area of industry and of services as well. What we’re experiencing here at this moment is similar to a smaller ‘village’ of startups. It’s the networking and the ‘nearness’ of these startups that’s special; the support that startups are giving each other. Everyone is willing to help each other out. From what I’ve experienced in Berlin, there’s more of a competitive mindset there. Adam Slade: What advantages do you think Hamburg has as a place to live, or for anyone looking for a developer job or engineering role, other than of course, being beautiful? Benedikt: I actually want to bounce that question back to you to give the readers a better understanding of your position and what your connection is to Hamburg. Adam Slade: First of all, I think it’s overlooked as a location. Back in 2018, when German startups set the record for the cash flow of over three billion euros that year, around 40% were in Berlin and 15% in Munich. Hamburg were sitting in third place at around 6%. It’s the third-largest tech hub in Germany but I was quite surprised by the number of developers that hadn’t considered it as a career location. So I wanted to understand how businesses in Hamburg have been growing their tech teams over the last few years, some of the challenges that they face, and then help to try to not only solve those but to share that information with developers across Europe that are looking to move to Germany. Companies like Airbnb had its first office in Hamburg and now you have Facebook, Twitter, Microsoft, much larger global giants that are moving to Hamburg and I see the evolution of the last five years only progressing into the next five. Hamburg has become a real contender for business founders. If you're looking for a new job in Hamburg, or you're planning to hire tech talent in Hamburg, reach out to Adam Slade.
The Start Up Ecosystem in Hamburg, Featuring Etvas GmbH
Adam Slade, Senior Consultant in charge of recruiting for Frontend & Backend jobs in Hamburg speaks to Ilie & Sören, Founders of Etvas GmbH about the growth of Hamburg as a Tech Hub in Germany, some of the resulting success stories, and how it compares to Berlin for development opportunities: Adam Slade: There’s more and more success stories coming out of Hamburg, in terms of its location for business. If you look back, of course, you’ve got businesses such as ABOUT YOU GmbH, Jimdo, Xing, FREE NOW (or mytaxi, as it was) and Airbnb had their first office in Hamburg. And, of course, you’ve now got Facebook, Microsoft, Twitter; all of these businesses seeing Hamburg as a location to build within. Ilie Ghiciuc: It’s a no brainer. There’s so much rain in Hamburg. There’s nothing to do but build companies! Adam Slade: Exactly! But, for me, when it comes to talking to the business founders, the developers, and the engineers in the market, it’s always ‘Berlin based’ conversations that I’m having; Berlin is seen as the tech hub. It’s seen as the tech capital of Germany. But as more and more success stories come out of Hamburg, do you the tide changing? Do you see Hamburg becoming more of a centralized tech hub, specifically in Germany? Do you see it becoming more attractive to potential business owners that are looking at building companies in Germany? Sören Timm: I believe that there are some big advantages that Hamburg has over Berlin; Hamburg has a smaller start-up ecosystem compared to Berlin. It's more interconnected. If you talk to a Hamburg investor, if you talk to the Chamber of Commerce and other entities within Hamburg, they’re really interconnected. So, you’re guided as a start-up to create to start your business there. So it’s good, at the start, to get some support. And these entities are doing this to create jobs in Hamburg, of course, in the tech space. So I believe it’s beneficial to have a smaller but really interconnected start-up ecosystem here. I think it will become even better if we get more accelerators and more VC’s in Hamburg. And the reason why I believe more start-ups are still registered in Berlin is because there’s more capital. So, I think where Hamburg could be better, is by having more capital in Hamburg to fund businesses or to finance businesses. But, in general, the whole gaming industry, in Hamburg has around four thousand staff; like Innogames. You already mentioned About You, My Taxi, Wunder Mobility, but also within Fintech, I believe Deposit Solutions GmbH is on its way to becoming unicorn, Exporo is there. So, there are also Fintech businesses in Hamburg. So, I believe it will get even better once there’s more capital in Hamburg. In terms of education, Hamburg is not a Metropol known for Computer Science, there are two universities but in one you can’t do your Masters. Maybe they could be more investment on that side. But the two universities are very good, so there are really educated people coming from there. However, in every large city there is a fight for talent and it’s the same in Hamburg but it’s an international city because of the Harbour, so English is widely spoken. Berlin is better, but it’s still good in Hamburg because of it being a trade city. Adam Slade: The reason that Berlin has such an attraction is because of that international culture. I think that following in their footsteps, Hamburg is certainly seen to be similar. And of course, like you said, what enables you to attract talent, is the ability to reach out across Europe as well; English speaking professionals, that wouldn’t have secure German-speaking opportunities and that gives you, as business owners, the chance to speak to these people as well. Ilie Ghiciuc: Which is exactly my case. I moved to Berlin two/three years ago. I remember just after I arrived, there was a statistic saying that Berlin has the most diverse tech workforce in the world. I don’t recall the exact numbers, but it was around 46% in Silicon Valley that are non-natives and in Berlin it was 48 or 49%. That’s pretty crazy when you think about it. I can only speak for myself, of course, but moving to Germany has been such a nice experience; everyone was so accommodating in Berlin and now in Hamburg as well. Everyone speaks English and is very nice. They want to find ways to work together and that is super, super cool. I think this is one of the things that I could imagine would be very important for Germany moving forward in the next year or two to continue to attract talent. Adam Slade: Yes, I agree. The developers that I speak to more so now are considering how a move to Hamburg could be a real business opportunity. I think two years ago it was certainly overlooked or overshadowed might be a better word, by Berlin. Volume-wise, there are more software companies in Berlin, but density wise it’s quite similar. So are around 2,500 listed businesses in Hamburg, or the head offices are in Hamburg, shall we say, and around 30% of those, in one way or another, have tech or software incorporated into their business model. So, they would be the sort of business that would hire an internal tech team. There’s around 5,700 companies in Berlin listed, so more than double, but it’s still around 30% of those that would have a tech team. So, it’s actually probably more promising to set up in Hamburg; there’s less competition out there as an investor or even as a business owner but you have the kind of same density. Ilie Ghiciuc: And I would add one personal note to this; in my opinion, Hamburg is one of the most beautiful cities in the world. I’ve been to many places and I can say that, as a place to live, it’s absolutely gorgeous. Too bad it only has 40 minutes of sunshine every year, but it is just a gorgeous place to be. I like it so much. Adam Slade: I think in a few years’ time, there’s going to be so many more success stories coming out of Hamburg. You mentioned Deposit Solutions GmbH, they’re on their way to hitting that Unicorn status. And, at that point, many people might think; ‘If they can do it, why can’t we? Many e-commerce platforms might look to Hamburg as a location. They might do so because there’s already so many well-established companies in Berlin that it actually would be quite intimidating to try and build a company in an area with so many potential competitors. So I, for one, certainly think Hamburg will certainly move in that direction, towards that status as a Tech Hub. If you're looking for a new job in Hamburg, or you're planning to hire tech talent in Hamburg, reach out to Adam Slade.
RecDoTech Podcast Episode 12: Mental Health in Tech - The Invisible Enemy with Will Falkowski Developer for 17 years
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/0yfBjfuD2JOrE63prgJRzi LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/mental-health-in-tech-invisible-enemy-will-falkowski/id1529453970?i=1000498853235 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3aQGvEL MENTAL HEALTH IN RECRUITMENT - THE INVISIBLE ENEMY After such a turbulent year, we thought it especially important to tackle the topic of the challenges that everyday life and work pressure pose on our mental health. Will Falkowski has worked as a Developer for 17 years for some great brands across multiple industries; retail, legal, finance, space to name a few. From his own personal experience and that of supporting others in tech who have suffered from mental health issues, Will has an extensive understanding of the topic and has founded JustaFriend.nl, a voluntary service supporting professionals in the industry. In our latest podcast with Lewis Adams-Dunstan, Will tackles this difficult but important subject with heartfelt honesty as well as lighthearted humour, covering: ✅ His journey as a developer and his own struggles with mental health. ✅ Imposter syndrome. ✅ The Highs Vs the Lows. ✅ How to spot a burnout. ✅ Just a Friend ✅ Advice for anyone that might not know where to turn Are you looking for a new Data science job in the US? Are you looking to hire in the US? Contact Lewis now for an informal chat, he will be happy to give you all the information you need. #mentalhealth #developer #podcast #recruitment #anxiety #depression #mentalhealthawareness #work #experience #wellness #health
Time to open up about Domestic Violence
Eden Whitcomb recently interviewed Isabel Städler, founder of https://www.louandyou.org/ about how they're using technology to support the victims of Sexual Assault and Domestic Violence. Check out the below video to find out how this amazing start-up is striving to improve the lives of countless people. Please share this far and wide so Isabel and her team get the support and funding they need to really kick this off! #Louandyou #Technology
Planning your Career Strategically
What are your career goals? Do you have a plan? When you choose your next job, do you choose it because it's a great, cool opportunity? Or do you choose it because it's a stepping stone to the job you want AFTER that? In our latest podcast with Kevin Goldsmith, he talks Lewis Adams-Dunstan through his journey to becoming a CTO. From Microsoft to Adobe to Spotify. Now he's the CTO of Anaconda, Inc. He talks about the mistakes he made along the way and the point where he decided to think about his career strategically. Here's just a snippet. #CTO #Technology #Career#Microsoft #Adobe
RecDoTech Podcast Episode 11 - The CTO Onboarding process with Kevin Goldsmith
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/2zaTQ5J18HUirZpTuVrpsI LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/the-cto-onboarding-process-with-kevin-goldsmith-anaconda/id1529453970?i=1000497454718 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3ttx4U3 **RECDOTECH PODCAST EPISODE 11** THE CTO ONBOARDING PROCESS There's a huge amount of diversity required from one CTO role to another; The job function changes wildly depending on the size of the company, headcount, business needs, etc. In this week's podcast, Lewis Adams-Dunstan talks to Kevin Goldsmith, who has recently joined Anaconda, Inc. as the CTO. With 25 years' experience, managing teams of 100+ people at global brands such as Microsoft, Adobe, and Spotify, we can't think of anyone better to advise on what's required to be a successful CTO. He also shares his recent experience of joining a business as a new CTO. In this podcast, Kevin and Lewis cover: ✅The journey to becoming a CTO ✅Planning your career strategically ✅The skills required to make a great CTO ✅What it's like joining an established team as a new CTO ✅Advice for businesses that are looking to hire a tech leader. You don't want to miss this one. Click this link to listen to the podcast now: https://open.spotify.com/episode/2zaTQ5J18HUirZpTuVrpsI #job #career #tech #microsoft #business #business #hiring #team #experience #recruiting #podcast #people
RecDoTech Podcast Episode 10 From dreams to reality- Build a data startup with Jacopo Tagliabue @ Coveo
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/0UDR83ytgPsLzrrJnhlg68 LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/from-dream-to-reality-build-data-startup-jacopo-tagliabue/id1529453970?i=1000496361842 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3rv8JeV **RECDOTECH PODCAST EPISODE 10** FROM DREAM TO REALITY - BUILDING A DATA START-UP "Building a company is a satisfying thing, but it is something that you need to WANT deeply. You need to make a lot of sacrifices and it's a long and sometimes painful and tiresome journey. Choose your travel companions wisely." In this week's insightful and amusing episode, Lewis Adams-Dunstan speaks to the brilliant Jacopo Tagliabue about his experiences of building a successful data start-up business, covering: ✅ An overview of Jacopo's journey from Ph.D. to starting and leading several AI start-ups. ✅ From a dream to reality - How to turn ideas into realistic and profitable opportunities. ✅ How to secure funding. ✅ Being acquired - What this means for the founders and their employees. ✅ Advice/best practices for entrepreneurs who are looking to build an AI Start-up. If you're looking to take the leap then you don't want to miss this episode! #AI #Startups #Data #Company
RecDoTech Podcast Episode 9: Leading Elite NLP teams with Imed Zitouni @ google
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/0Lc2R8YRNDZ7o9udghNZ2o LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/leading-elite-nlp-teams-with-imed-zitouni-google/id1529453970?i=1000495419814 LISTEN ON GOOGLE PODCASTS: http://bit.ly/2YKxuXR THE FUTURE OF NLP WITH IMED ZITOUNI @ GOOGLE Imed Zitouni is the Director of Engineering at Google and in our latest episode, Imed speaks to Lewis Adams-Dunstan about building Elite NLP Teams. Imed has a Ph.D. in Computer Science and in our LATEST PODCAST EPISODE he draws on the experience gained throughout his extremely impressive career, working with some of the world's most prestigious businesses, to discuss the following: ✅ His journey through tech to NLP ✅ The evolution of NLP; human and computational understanding ✅ Driving innovation at a leading tech business. ✅ The future of NLP. ✅ Advice for NLP as tools for business. Here is just a snippet but you don't want to miss the full podcast episode! #NLP #Technology #Computerscience
RecDoTech Podcast Episode 8: Data science - A Woman’s Perspective with Maria Ovchinnikova @ portchain
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/5ch7ZYuDj7ANOVbfMBCbnk LISTEN ON APPLE PODCASTS:https://podcasts.apple.com/us/podcast/data-science-womans-perspective-maria-ovchinnikova/id1529453970?i=1000494859846 LISTEN ON GOOGLE PODCASTS: http://bit.ly/2MUL0Wk RECDOTECH PODCAST EPISODE 8 DATA SCIENCE - A WOMAN'S PERSPECTIVE Maria Ovchinnikova is an inspirational tech leader who has gone above and beyond in a drive to bring more women into the tech arena. As a Product Owner at Portchain and the Founder and CEO of WomenHackCPH, Maria is dedicated to closing the gap between academia and industry by helping young female developers, data scientists, enthusiasts, and STEM graduates to apply their knowledge to real-world business problems. In our latest podcast, Maria talks to Luke Parkinson about: ✅The transition between education and the workplace. ✅Combating the isolation of an un-diverse environment. ✅The lack of understanding of Data Science as a career path. ✅Solving business problems with WomenHackCPH. ✅Tackling unconscious bias. #Datascience
THE FUTURE OF NLP WITH IMED ZITOUNI at GOOGLE
Imed Zitouni is the Director of Engineering at Google and in our latest episode, Imed speaks to Lewis Adams-Dunstan about building Elite NLP Teams. Imed has a Ph.D. in Computer Science and in our LATEST PODCAST EPISODE he draws on the experience gained throughout his extremely impressive career, working with some of the world's most prestigious businesses, to discuss the following: ✅ His journey through tech to NLP ✅ The evolution of NLP; human and computational understanding ✅ Driving innovation at a leading tech business. ✅ The future of NLP. ✅ Advice for NLP as tools for business. Here is just a snippet but you don't want to miss the full podcast episode! #google #engineering #nlp #future #computerscience #computer #technology
RecDoTech Podcast Episode 7: Hire and Build a Data Science Team with Graham Morehewr @AON
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/4WOOvrNfBffCqXkaPTDKXn LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/hire-build-a-data-science-team-with-graham-morehead-aon/id1529453970 LISTEN ON GOOGLE PODCASTS: http://bit.ly/39JI2No In our latest 'Preparing the Unprepared' webinar, Lewis Adams-Dunstan speaks to Graham Morehead, computational linguist, and Principal Research Scientist at Aon about HIRING AND DIRECTING A DATA SCIENCE TEAM. In the first snippet from the interview, Graham covers... WHAT DOES IT TAKE TO BE A GREAT DATA SCIENTIST? "Many assume that they can go to a code camp to learn how to be a Data Scientist. And that is definitely a great place to start. But I've been in Data Science since the last 1990s, and I still only know 10-15% of what there is to know about the field. There are some basic tools that every Data Scientist should have; Common language skills; Python, Pytorch, TensorFlow. They should also have of the current algorithms, what backpropagation dows, what the popular neural networks do... But every data Scientist should find the one thing that they are drawn to. If you take 2 highly skilled people, who are equally matched, talent-wise, but one has PASSION about what they do, there's your front-runner!" #datascience #datascientist #datascientist #machinelearning #bigdata #deeplearning #deeplearning #artificialintelligence
RecdoTechPodcast Episode 6: Mothers in tech with Gayle @ Amazon, Brandee @ Appetize and Kate @ DATAcated Academy
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/1COAyr05QZtNj69XkMAEhZ LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/mothers-in-tech-gayle-amazon-brandee-appetize-kate/id1529453970?i=1000493102628 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3jiHxNn REC DO TECH PODCAST - EPISODE 6 **SPECIAL EPISODE - MOTHERS IN TECH** "It's the biggest project management job ever. You're juggling a lot of balls at once; some are plastic, some are glass. You just need to make sure you catch the glass ones." In this week's special episode, we're talking to Brandee Sanders - Senior Director Marketing Operations @Appetize, Kate Strachnyi Founder DATAcated Academy, and Gayle Gallagher - Snr Manager- Marketing- EU Special Projects Amazon. These inspirational ladies chat with Darwin's Lewis Adams-Dunstan about how they balance being a mother with being a Senior Woman in Tech. #Technology
What makes the hiring process toxic?
WHAT MAKES A HIRING PROCESS TOXIC? "When you're weeding out as many applications as possible, rather than trying to bring in as many as possible, that is the SEED OF TOXICITY in the hiring process!" Lewis Adams-Dunstan and Vin Vashishta, Chief Data Scientist at VSQUARED discuss this 'taboo' subject in our latest 'Preparing the Unprepared' webinar. Vin also asks a very good question.... "Do you make hiring decisions in the morning or afternoon?" And he, rightly, points out that... If you're in Data Science or Machine Learning, by the afternoon you've made HUNDREDS of complex decisions, so should you really be making another? You're DECISION FATIGUED!" Stay tuned for the full podcast episode with Vin, as we also cover: - How to spot toxicity in a Data Science Team. AND - Behavioural practices that create better processes and increase hiring success. Watch the snippet below. We'd love to hear your opinions. #datascience #datascience #datascientist #machinelearning #hiring #leadership #team #webinar #podcast
RecDoTech Podcast Episode 5: Making Smarter Tech Career Decisions with Ben Taylor & Data Robot
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/5T7XZnYcT9MwpHK0BWu9aR LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/making-smarter-tech-career-decisions-ben-taylor-datarobot/id1529453970?i=1000492126909 LISTEN ON GOOGLE PODCASTS: http://bit.ly/39Lb0wb RECDOTECH PODCAST EPISODE 5 AVAILABLE NOW **Making Smarter Tech Career Decisions with Ben Taylor (click 4 sound) @ DataRobot** "An interview is short and a resumé is much shorter. Your resumé will hold someone's attention for 5-30 seconds. With algorithms, you might not get looked at, at all. You could get screened out.' So how can you build your profile so it is seen by the right people? Ben Taylor (click 4 sound), Chief AI Evangelist at DataRobot offered his expert advice, in the latest episode of the RecdoTech podcast with Lewis Adams-Dunstan. He gives his opinion of the different ways to boost your profile in the tech space covering all areas; From MeetUps, blogging and Kaggle, to internships, consulting, and engaging in Open-Source projects. If you're looking to boost your profile, you don't want to miss this one.
Brian Bell On Building DataRobot In Denmark, Secret Behind DataRobot, Product Delivery + A Lot More!
With major progress in the AI market it is likely we will see big changes happening in our lifetime. Are you interested in AI? We would love to hear your opinions and predictions on the future of AI! Make sure to comment below. If you want to hear more about AI dont forget to check out the full interview with Brian Bell here #datarobot #productdelivery #denmark 'AI
Interview feedback - Let's talk about GHOSTING...
"If you're an organisation that is intending to grow, do you help or hurt your brand by providing constructive feedback after an interview?" This was the topic of conversation in the latest "Preparing the Unprepared" interview with Lewis Adams-Dunstan, Abigail (Abby) Shockley, PhD, Data Science lead at Petram Data and Chad Oda, Partner at Chatmode. Many businesses are really hesitant to provide negative feedback after an interview. Why is that? Could it be caused by having too many interviewers in a panel interview, so the feedback is nigh on impossible to aggregate? Maybe there are liability or compliance concerns about giving negative feedback (recruiters alleviate that risk...) Maybe, it's just easier all round to send a generic "Sorry, you haven't been successful" message. But is that helpful to anyone? It doesn't help the candidate, or maybe even the employer brand, for sure.
RecDoTech Podcast Episode 4: Building a personal brand in tech with Eric Webber @ Yelp
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/3vH3mSLBzL5KMdqGCWDNGR LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/building-a-personal-brand-in-tech-with-eric-weber-yelp/id1529453970?i=1000491312949 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3cGZ8gQ Building a strong personal brand requires dedication to creating original content on a regular basis. Right? Wrong! 'You can build a brand and a sense of who you are in terms of the comments you put out there and the questions you ask of other people. It doesn't have to be original posts.' These wise words are from Data Thought Leader and GM of Experimentation and Data at Yelp. If you're looking to build your personal brand, then you NEED to check out this video. It's the first in the series from Eric, so stay tuned for more....
RecDoTech Podcast Episode 3: Creating Unbiased Working Environment with Sarah Novato @snap inc
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/0VBQNTCFVe97F6ejTTJxL6 LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/creating-unbiased-working-environment-sarah-noovari/id1529453970?i=1000490461353 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3cJcjxE Can AI help to bring efficiency to the HR process? Can it help to tackle affinity bias? Will it eventually automate the hiring process? Will we ever be able to trust an algorithm to take responsibility for a process that will, inevitably, be called into question time and time again? Is it more trouble than it's worth? We LOVE this interview snippet because each of our speakers has a different opinion: Lauren is all for it! She believes that AI could be fantastic, and longs for the day when an algorithm can eliminate affinity bias. Lewis is totally against it. He believes that only a human should be responsible for a process that heavily affects human lives. Sarah @Snap Inc. plays a wonderful 'devil's advocate', calling upon her knowledge and experience to mediate the debate and offer her expert opinion. # You don't want to miss this one and you can listen to the full episode on our podcast on Spotify or Apple Podcasts.
Implementing Lean Methodology into an Agile Start-Up
Are you looking to start a new project? Maybe even build your own start-up? This is part 1 of a Lean Methodology series with Eden Whitcomb and Lorenzi Di Nobili, CTO of start-up Grazie (https://saygrazie.com/). In this first installment, Lorenzo, a highly skilled engineer, and Eden discuss the fundamentals and key teachings of the Lean Methodology. Stay tuned for part 2, which discusses how to understand and avoid vanity metrics. Part 3 explains how to embrace MVP as a mindset. If you want to listen to the full interview you can do so by subscribing to the RecdoTech podcast that is now available on Spotify and Apple Podcasts:
RecDoTech Podcast Episode 2 First Steps of Lean Methodology - Testing Your Hypothesis
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/1woIRYmuulHWjdOddtQH1H LISTEN ON APPLE PODCASTS: RecdoTech: Implementing Lean Start Up Methodology with Lorenzo Di Nobili, Founder of Grazie on Apple Podcasts LISTEN ON GOOGLE PODCASTS: http://bit.ly/3rjc68w In this episode Lorenzo De Nobili explains specifically what his own start-up Grazie ( https://www.saygrazie.com/ ) does and how as a young company, they are testing their hypothesis and developing their #mvp whilst using the #leanmethodology Some takeaways in this video cover the idea of using #landingpages as MVP's to understand market fit as well as a bench mark for conversion rate! Check out the full video below:
RecDoTech Podcast Episode 1: Women in AI Dr. Nancy Ranxing Ali PH.D
**LINKS TO THIS EPISODE OF THE RECDOTECH PODCAST** LISTEN ON SPOTIFY: https://open.spotify.com/episode/0QegK7NvjwkIh6edvv1bBW LISTEN ON APPLE PODCASTS: https://podcasts.apple.com/us/podcast/women-in-ai-with-dr-nancy-ranxing-li-ph-d/id1529453970?i=1000489298144 LISTEN ON GOOGLE PODCASTS: http://bit.ly/3tlXreJ We've finally launched our PODCAST!! Our first episode features Dr. Nancy Ranxing Li Ph.D. Dr. Nancy Li was the youngest student ever in her Ph.D. program and she is now the Director of Growth at Cox Communications, previously the Group Product Manager at Verizon. In this episode with Lewis Adams Dunstan, Nancy takes us on her journey from Ph.D. and her early career in fashion design to where she is today and the hurdles along the way..... "Her background is in fashion design. What does she know about engineering??" "She's a Ph.D. What does she know about business??" Nancy feels that she's had to rely on her influencing and negotiation skills to get where she is today. Make sure you subscribe as we'll be launching an episode per week. Our next episode will feature Sarah Nooravi, Senior Financial Analyst @ Snap Inc, on the subject of 'Creating an Unbiased Working Environment.'
Taking your first step in Data Science with an unconventional Degree
This week, Lewis speaks to Angela Baltes, Institutional Data Scientist at The University of New Mexico about how she forged a successful career in the field with (what some might perceive as) an unconventional degree. How do you take your first step into Data Science if you have a degree that doesn’t normally come to mind when you think of a Data Scientist? Angela, who NOW has a PhD in Biomedical Informatics, entered the field with a Bachelor’s in Criminology as well as qualifications in Public Administration and Information Technology. Angela says her PhD has changed how she sees and approaches Data problems but doesn’t believe that it’s totally necessary. It was Angela’s Bachelor’s in Criminology that instigated her passion for analysing Data. But how did she take the step into Data Science? Click on the video below to find out. ..
What does Divesity Mean when hiring for Tech teams?
What does Diversity in the Workforce actually mean? "It doesn't just mean hiring more women into the team. It's more nuanced than that. Women are certainly a part of that. But it's about incorporating all under-represented minorities. We're also talking about diversifying in terms of age." Lewis Adams-Dunstan talks to Sidney Madison Prescott Global Intelligent Automation Lead at Spotify about what it means to build a truly diverse tech team. This is the first in a fascinating series of videos with Sidney so stay tuned. You can view the full interview here.
Data Interviewing - Hiring Manager Involvement
"Whether you're a hiring manager now or in the future, or you're advising a hiring manager... Their involvement in the process is really important. The more actively you're involved in defining the job description, the better. You're going to get out of it what you put into it. A lack of involvement from the hiring manager is setting someone up for a quick exit!" In today's video, Lewis Adams-Dunstan continues his conversation with Eric Weber, Head of Experimentation at Yelp and Data thought leader. This time, they're discussing the importance of hiring manager involvement in the recruitment process. To what the full video 'The Data Driven Recruitment Process,' you can find it here: https://www.youtube.com/watch?v=BQ5xiAHQztE
Interviews are part of the onboarding process
"The recruitment process, plus the first 90 days of employment really determine how long you're going to stay at the company But sometimes hiring gets crammed into an already tightly packed schedule. And think of how that time pays off... If you hire the right person. It's HUGE!" Lewis Adams-Dunstan talks to Eric Weber, Head of Experimentation Yelp and Data thought leader, about why it's so important to have a great recruitment process from start to finish. Click here to view this snippet, with more coming later this week. To view the full 'Data Driven Interviews' webinar, the link is in the comments.
A Clear Passion and a Strong Network Will Drive Your Career
"JOB DESCRIPTIONS DON'T MATCH TO REALITY. They're collated from a panel of input and then thrown together. That's the problem. Taking a panel of feedback for a job description gives you multiple perspectives packed into one job spec. Now you're looking for someone who doesn't exist. You're also creating a gender bias." So, as a job seeker? How can you possible hope to make it to the final 3? Ben Taylor, Chief AI Evangelist at DataRobot discusses this problematic process with Lewis Adams-Dunstan and offers his advice for job seekers in a competitive market: "If you're an applicant who is coming in through the main funnel, then you're likely to be disqualified. People take a lot of pride in their resume but there are 100 people who look just like you on paper. So, how do you stand out?" Watch the full video below to find out...
An interview isn't enough. you need to boost your profile
"An interview is short and a resumé is much shorter. Your resumé will hold someones attention for 5-30 seconds. With algorithms you might not get looked at, at all. You could get screened out.' So how can you build your profile so it is seen by the right profile? Ben Taylor, Chief AI Evangelist at DataRobot offered his expert advice, in a recent webinar with Lewis Adams-Dunstan. He give his opinion of the different ways to boost your profile in the tech space covering all areas, from MeetUps, blogging and Kaggle, to internships, consulting and engaging in Open-Source projects. If you're looking to boost your profile, you dont want to miss this one. Check out the video below.
Top Tips for Building a Personal Brand
In the last in our mini webinar series with Eric Weber, Data Thought Leader and GM of Data Science at Yelp, he gave us his top tips for building a personal brand: 1. Start in ONE SPOT. Don't try to tackle multiple channels at once. 2. Build things organically. 3. It's a marathon not a sprint. 4. Set a schedule. 5. Be consistent. 6. Understand who you want to be. 7. Post about your everyday experiences and challenges. 8. Be HONEST! If you dont understand something, ask your network. 9. Build a rapport. BUT THE TWO BIGGEST TAKEAWAYS ARE: Consistency is key and consistency is key; people want to be able to contribute to the conversation. For more information around each of these great tips, what the full video below. What would your top tip be? Comment below. We'd love to hear from you. #personalbrand #datascience #thoughtleadership #recruitment
The POWER of a Strong Personal Brand
"Things are changing around the globe. From now on, companies will be more open to pursing talent where it exists, not where they want it to exist. So, your online personal brand is more important than ever." Eric Weber, data thought leader and GM of Data Science at Yelp said this in our latest installment from our webinar with Lewis Adams-Dunstan on building your personal brand. But where do you start? It's a daunting prospect if you're not already that active on social media. Right? Eric goes on to say that: "It doesn't take tens of thousands of followers or connections. What matters is the QUALITY of the connections you have and how you engage with them," Watch the full videor below. The final installment of this fantastic series will be posted next week. So stay tuned...
Remote Working Webinar - Adapting your business, Increased Marketing and Forging Relationships
"We've pumped up marketing like like mental over the last two months. I have three hours of calls with marketing." Bradley Wilkins chats to Ajey Anand at Norigin Media about how they're ramping up their marketing to be able to ride the effects of the Coronavirus on the Broadcasting industry. If businesses have really cut back on Marketing in recent months, how are they planning to increase Marketing activities when it becomes crucial to do so? We'd love to hear from you.
Remote Working Webinar - Traditional Methods of Communication are Vital
'Traditional methods of communication are vital to support Zoom/Slack' We've posted a lot recently about why it's vital that, whilst we're all working more remotely, we use a diverse range of communication methods to keep in contact with our team members to ensure that they continue to feed valued and motivated. Eden Whitcomb recently spoke to Wouter Verhoog at HUMANOO about why this is particularly important for his business. Watch the video below. Thanks for sharing your insights Wouter.
Remote Working Webinar - The Pros and Cons of Continued Remote Working.
"When things go back to normal, what really changed in your company?" Klederson Bueno from Minespider asks that question in our latest webinar with Eden Whitcomb. How much or how little did you innovate? Was innovation limited to technology? Everyone is talking about huge digital transformations, but has the transformation been more cultural? Klederson believes that one of the biggest things to come out of remote working, is the lack of recognition. As a result, will we see an increase of 'imposter syndrome'? Will staff actually prefer to be in the office after spending so much time working alone? It's such an interesting discussion. We recommend that you watch the full video below.
Remote Working Webinar - Supporting Mental Health Wellbeing Remotely
The mental wellbeing of a workforce is important at all times. But in the current climate, it's undoubtedly more difficult to monitor the wellbeing of our staff, when we're all working remotely. Eden Whitcomb spoken to Brighter AI about how they've put processes in placed to ensure their employees feel comfortable and supported. Thank you Teodora Suciu for sharing your thoughts. You can watch the webinar below. How have you been supporting your staff throughout the lockdown period? How has your employer been supporting you? We'd love to hear from you. #healthcare #covid19 #workfromhome #socialdistancing #workingremotely #remotework #remoteworking #hrtips #recruitment
Remote Working Webinar - Will many businesses follow Twitter, Shopify and Upwork?
What precentage of your business will continue to work remotely, in the long term? How many of you now view remote working differently? My hand is up... With companies like Twitter, Square, Shopify and Upwork announcing just recently their plans for a full remote workforce, how many businesses will follow suit? Has our way of working changed forever? Eden Whitcomb discussed this with Lisa Dempsey, CPCC and the exciting opportunities for the future with regards to diversity and inclusion. What are your thoughts? what would you like to see happen? We'd love to hear from you! #workfromhome #workingremotely #workingfromhome #remoteworking #remotehiring #remoteworkforce #remote #diversity #inclusion #diversityandinclusion #berlin #germany #technews #twitter #shopify #square #upwork FULL TRANSCRIPTION: Eden: Welcome and thanks for joining us. You are here today because you believe that information and knowledge sharing is critical in a connected world. Our goal with this show and company is to introduce high quality, actionable insights that will help both hiring managers and job seekers execute lean recruitment processes and gain industry knowledge to further enhance their careers. Today, I am joined by leadership coach and Human Dynamics and engineer with more than 20 years experience delivering results in fast paced global organizations, specifically working with purpose focused individuals, teams and businesses who want to make an effective and positive impact on the world. Right now, she's the CEO of her own business; Leadership Labs, as well as an advisory member to the board of three other organizations. She also hosts her own podcast; H.R. Matters and provides low cost webinars to help organizations pivot through times of crisis and make working virtually more meaningful and impactful. I've been a fan of hers for some time and it's an honor to share the call with her today. So please welcome the winner of the Gold Leader Award for her Visionary Leadership, Lisa Dempsey, CEO of Leadership Labs.Add Speake Welcome to the show, Lisa. How you doing? Lisa: Thanks so much for having me on, Eden. It's a pleasure to be here with you. Eden: We've been remote working, and companies have responded, at least from what I've seen in Berlin, reasonably well. I mean, you know, they had to change quite quickly overnight to a new process. There are some hiccups or some teething problems, but near enough, everyone I've spoken to have made it work. Do you think that we're now stepped into a new way of working for the remote and home office specifically is going to be the new norm to the workforce? Yeah, I think that's one of the big questions that's out there right now, you know what what are going to be the the habits and things we're going to carry forward out of this? Lisa: There's a great graphic that's running around out there with the question of, you know, what was the source of your company's digital transformation, your your CEO, CTO or COVID 19. I think a lot of people are recognizing that, you know, this really has caused a lot of digital transformation, forced transformation. What I would hope is that companies would find really useful ways to be able to work remotely together. It opens up a lot of doors, a lot of opportunities. It requires some attention and focus to figure out how to do it well. And that's why I I'm actually getting ready to release my very first public workshop on that. It's really valuable, but you need to get it right and you need to do some really specific things. I think there will be some backlash. There will be some teams that will be so happy to get rid of whatever digital tools they've been using. They'll want to only have face to face for some period of time. But hopefully, you know, this is brought it's taught some companies that have been maybe more traditional in that and resisted it more in the past to the possibility and the potential and that they it is you can have a really effective global workforce collaborating well without having to bring them together all of the time. You know, I think some people will be will be happy to resume some of their business travel once that becomes safe. But hopefully there will be really fun, effective digital spaces that will start opening up to people in those stores have now been opened. And that will continue to grow because I do think that it's. It's not the only tool. It's unfortunate that right now it is the only tool available and that's creating some frustration. But when you mix it in with a variety of tools and possibilities, it's really good. There's a lot of value in it But I'm most looking forward to seeing the spike in businesses open and open up to more home office. But then also driving diversity and inclusion into that business is way more than we were previously doing it. And specifically, diversity in within the tax base I work is is a big topic. Eden: You see many businesses wanting to do it and wanting a diverse workforce, a more inclusive workforce. They're struggling to do so. Hopefully now with the Home Office, they can hire people. That's kind of where you are and have that opportunity to make it a truly diverse workforce and not just based on nationality, but, you know, gender, race, nationality, whatever. And having for the first time really on en masse, the chance to do that must be almost looking forward to. It just needs to be done. I think a lot people would drive in that. And I'm excited for that. But it needs to be like you. You said there's a lot of working components to go into, actually a true blend of home office and work office. So it's make sure it's done right. And you're kind of taken by as many people as possible and run with it for as long as possible. My biggest fear, I think, with this is we just go straight back to normal and there'll be a complete disengagement from some kind of sea level through town to jobseekers where we went when the office was we went to work at home and like almost cautioned against each other too much. That's a fear that I think I probably have seen this advising businesses to kind of be a bit more receptive, be a bit flexible now because we've proven they can work and it is working with the vast majority of companies, whether or not they're telling me because we're on video. But the majority of companies have seen similar, if not better, productivity levels than when they're in the office. So fingers crossed, kind of. We see a new world of workforce emerging after this. Lisa: Yeah, I certainly hope so. You know, I genuinely hope so. And I love what you say about, you know, the hopefulness that that is out there and and people really being hungry for that. Now, I would encourage everybody who who has had positive experiences and even the negative experiences kept purely intentional about where you want to go from here. As we start building a different normal, as we start shifting back to something other than 100 percent distancing and isolation, get really intentional about what it is that you want to continue doing, that you have found that that works in an equally does it? That's the most important way to really co create the future that we want to build together. Those voices need to be heard in and businesses need to to understand what it is that that has opened up so that that can be used really efficiently and effectively in really clear and intentional ways as we as we go forward. We don't have to go back to the old way of everybody in the office, That's not necessary.
Remote Working Webinar - Skills that make up a great remote worker
What skills are required to be a successful remote worker? We envisage that remote working will be far more common within many businesses in the future, opening up the opportunity to hiring from overseas. But not everyone has the skills, or drive required to be a truly successful remote worker. We kick of the week with another webinar from Eden Whitcomb and Katya Christina Eckert from Humanitec where they discuss the attributes that make up a great remote worker. Stay tuned for more webinars, discussing the current situation, later in the week. FULL TRANSCRIPTION Eden: Today, I'm joined by an extremely passionate and warm individual who has found her colling in the mix between digitization and its impact on people and businesses. Over the past four years, she's been working on a platform aimed at allowing developers to focus on real engineering problems rather than wasting time figuring out how to get their code into various environments. It's always a pleasure speaking with her. Please meet Katja Eckert's co-founder of Humanitec. Welcome to show. How are you doing? Katya: I'm very well. Are you. Eden: Yeah. Very well, thank you. We're still still working remote, two and a half weeks left to go, minimum here in the UK. How are you and the team finding the remote setting at the moment? Katya: think we're adapting quite well. We are a smaller team of a size of 20 people. So I think that really helps us to stay in touch and to basically organise the overall setup quite smoothly. Eden: So what specific tools you use at the moment to allow the transition? Katya: Yeah. So I think we've already well set up. We have what used to work with the developers in Kenya. So we were already quite experience in what it actually means to be in different offices and speaking remotely with each other. So we're using slack on a day to day basis. We're using Google Hangouts for calls. And so we also basically starting to use zoom her and there. And we really make sure that we also use our documentation tools and we record the meetings. Yeah. Stay stay up to date with everything that we do in the best way possible. So the tools we're using is definitely the absolute basis of everything of our day to day life. So what skills do you think somebody needs right now? What do you need to develop to be an effective remote worker? Yeah. From what I've seen on the team, I think self-motivation. That means sleep enough and eat healthy, get some fresh air, do some work, exercise. I really think keeping your brain awake during the day to day tasks that you have your company, I think that's essential and that's something that drives self motivation. I think if you feel good in life. And if you feel good at work, because if this comes together, I think your motivation level is absolutely higher. Obviously, you're on your own in your own area. So I think self motivation goes together with being working independently and being able to write properly. So I think strong written communication skills are probably even more important than general verbal communication skills, but it's a mixed cultural environment. So you speak with your teammates in a cultural setup that's ever might has different sender and recipient understanding. That is something in that in the 'in-person' environment, speaking with your hands and your emotions. That is something that I think normally is easier to not have a misunderstanding. I mean, there should be always some comfort in learning and using any kind of digital tools, introducing new digital tools. Yeah, I assume that these are, from my perspective, the most important skills for remote setup. Eden: Yeah, definitely. Great. The communication aspects. I mean, anything that anything written down can be mis-interpreted in a completely different way from what the person means and then it causes some issues down the line. So I definitely encourage my team to least pick up the phone. Give a skype call. Whatever method they choose.
A message from some of our people
A short message from some of the team here at Darwin Recruitment. Over the last few weeks, we've seen some amazing examples of businesses who have, despite the challenging times we're in, been able to adapt their business models and continued to grow. Recruitment has definitely slowed but it hasn't stopped. We've have been working closely with organisations all over the world to keep their processes and hiring plans running as smooth as possible; interviewing and onboarding remotely. Thank you to everyone in the Darwin team for your hard work and to the clients we support and the fantastic job seekers we help.
Remote Working Webinars - Managing Stress in Unusually Stressful Times.
How can you manage the stress levels of yourselves AND your employees in an unusually stressful time? Eden Whitcomb speaks to Lisa Dempsey, CPCC about her top tips for understanding what is making us overly stressed and how to combat those issues. The top two things that stood out for us, were: 1. Don't work long hours; whilst it is tempting to 'just finish one more thing' it's very important to keep the same hours as you would in the office. 2. Make full use of outdoor time; ensure you get OUTSIDE to exercise every, single day. Fresh air is as important as the exercise itself. Watch the full video below as Lisa expands on the above as she has many other insightful bits of advice for managing stress in an unprecedented time. What are you doing to manage your stress levels? We'd love to hear from you. FULL TRANSCRIPTION: Eden Whitcomb Welcome and thanks for joining us. You are here today because you believe that information and knowledge sharing is critical in a connected world. Our goal with this show and company is to introduce high quality, actionable insights that will help both hiring managers and job seekers execute lean recruitment processes and gain industry knowledge to further enhance their careers. Today, I am joined by leadership coach and Human Dynamics and engineer with more than 20 years experience delivering results in fast paced global organizations, specifically working with purpose focused individuals, teams and businesses who want to make an effective and positive impact on the world. Right now, she's the CEO of her own business Leadership Labs, as well as an advisory member to the board of three other organizations. She also hosts her own podcast; H.R. Matters and provides low cost webinars to help organizations pivot through times of crisis and make working virtually more meaningful and impactful. I've been a fan of hers for some time and it's an honor to share the call with her today. So please welcome the winner of the Gold Leader Award for her visionary leadership, Lisa Dempsey, CEO of Leadership Labs. Welcome to the show. Lisa, how you doing? Lisa Dempsey Thanks so much for having me on Eden. It's a pleasure to be here with you. Eden Whitcomb With the whole fear aspects and the energy drain, you also touched upon the fact of stress as well. And stress in the workplace is massive in any circumstance, in a circumstance where the whole economy seems to be crashing down around us, you know, it's just causing more stress to everybody from every department. So I know this is something that you've been working on quite a lot recently. So is there any specific, actionable insights? Anything that companies can do right now to help minimize distress outside of what you discussed, Is there anything else that you could recommend to somebody, say, look, if you've got stressed individuals or stress team or workflows, try these sorts of tactics in terms of stress management? Lisa Dempsey: There's some really basic things that people can be doing, really straightforward. And it's especially important in terms of working virtually. So really taking the time to connect with people on a personal level in doing it fun novel, things like taking a virtual tour of a colleagues home or meeting their kids and getting to know them is something that I've heard a lot of feedback on from people as well, that in a remote working has been difficult. But it's been so nice to see their colleagues as like real people with stories and families and all of these things build on that connection. Clear space for self reflection. It's a really important part of doing and it's really, really important in terms of stress, because, again, you've got to tune into what's going on inside of you to be able to name it, to be able to recognize, you know, my feeling more tired today. Am I feeling more stressed today? My feeling more fear today. You've got to make time for that. And so clear some space and it doesn't have to be long. It can just be two minutes when you wake up in the morning or, you know, 30 seconds before you step into an online meeting. Another thing people can do is get outside. If you're in a country and you're in a space where allowed to be outside. Get out from behind your screen. Your brain needs this to be effective. Focusing on just sort of that the the twelve inches or the, you know, half meter between your body and your screen. That'll lead to tunnel vision no matter what. So kid out if you can get outside, create a daily routine for yourself. You know, we've had all of our normal structures ripped out, creating just a daily routine and rhythm for yourself, whereby you're waking up at certain times, you're working in certain blocks of time. It's so easy when, you know, we're basically our home becomes our office and there's all of this work and we're trying to fill all of these gaps. It's easy to trick ourselves into believing that working more hours is going to make us more effective. Now that that has never been true and it never will be true. So, you know, block out your working times and build a schedule for yourself. And remember everything in moderation, including moderation and ask for help. You know, this goes back to her as well. The the a little bit of the example that you gave, ask for help, ask, you know, get curious about the things that you're really struggling with and you just don't know you feel lost and are unsure about. Don't bottle it up and pretend that everything's fine. Ask the important questions, even if they're hard and uncomfortable. Letting that in does wonders and can really release a tremendous amount of stress and create a lot of opportunity. And then the last thing that I would really hope for everybody is laugh, you know, find. Find something funny. Find some humor or share humor with your colleagues. Not obsessively. I know some some teams have said, oh, I'm constantly getting nothing but funny You know what? That messages from somebody. It's this constant stream and it's it's tiresome then. But that's not helpful. But, you know, making time to laugh and just enjoy something, you know, at least once a day. It reduces stress and it increases memory. So it's really important to just find a moment to laugh, relax every single day.
Remote Working Webinar - Operating under Dimished Capacity
'We're all working with diminshed capacity, whether we feel it or not.' Maybe you're juggling home school as well as working. Maybe you're trying to fit everything into reduced hours. Or, like everyone else, its a natural response to the trying times that we find ourselves in. Managers, business owner and even us as individuals need to understand that and try to avoid putting undues pressure on ourselves and others. Eden Whicomb discusses this in more depth with Lisa Dempsey, CEO of Leadership Labs International and Co-Founder of HR Matters Podcast. FULL TRANSCRIPTION: Eden: Welcome and thanks for joining us. You are here today because you believe that information and knowledge sharing is critical in a connected world. Our goal with the show and company is to introduce high quality, actionable insights that will help both hiring managers and job seekers execute lean recruitment processes and gain industry knowledge to further enhance their careers. Today, I am joined by leadership coach and Human Dynamics and Engineer with more than 20 years experience delivering results in fast paced global organizations, specifically working with purpose focused individuals, teams and businesses who want to make an effective and positive impact on the world. Right now, she's the CEO of her own business, Leadership Labs, as well as an advisory member to the board of three other organizations. She also hosts her own podcast; HR Matters and provides low cost webinars to help organizations pivot through times of crisis and make working virtually more meaningful and impactful. I've been a fan of hers for some time and it's an honor to share the call with her today. So please welcome the winner the Gold Award for her visionary leadership.Lisa Dempsey, CEO of Leadership Labs. Welcome to the show. Lisa, how you doing? Lisa: Thanks so much for having me on Eden. It's a pleasure to be here with you. Eden: So what can companies be doing right now, I guess, to ensure that energy levels are high, energy wastage is low or as minimal as possible? Is there any kind of effective steps that you've taken with the companies that you are coaching around that obviously, as you're saying, the structure is important, having that transparency, but what else would you kind of advise people to be doing at the moment? Lisa: Yeah, I think this is such an important question, because managing our energy levels is the most valuable thing that we have in any circumstance. But because it's even more important in times of crisis, there's a reality that we're facing right now of everybody is working with diminished resources. You know, our brains and bodies have been told, hey, there's danger out there. There's this invisible, teeny, tiny microscopic germ, you know, virus that can harm you and your family. So that means that our brains and bodies are part of it has gone into a kind of crisis management and survival mode. So really, the majority of people are are working with slightly diminished resources, whether they realize it or not. You can't really kind of deny that the impact that that has. And it's just a very natural survival instinct. So recognizing that, you know, even in the best of circumstances, even if you're doing everything absolutely right, you're going to be working with slightly diminished resources is really important because accepting that and accepting that, that means that everyone's going to have an individual response. There are going to be ups and downs. And just allowing the space for that, allowing the compassion for the reality of that is so important, because when people there's something that happens to us in our brains and bodies and this is a part of the neuroscience that I bring to to my coaching is just even being able to name it, being able to say, you know what, team? Today I'm feeling really tired and feeling really stressed out. You know, I heard from a friend that somebody was really sick or heard something on the news that really disturbed me and made me think about things in a really different way. Whatever it is, just being able to name it and not be judged were it not have to go into problem solving or fixing that, but just call it out, brings huge relief and releases a huge amount of energy and stress. So there's really that that knowing and accepting is is the first and most important step. Then, you know, it's again, about creating cohesion, you know, understanding that you as a team and as an organization can still create a number of things, even if you're working with diminished capacity and resources. But again, co creating that together with teams, asking people do they know what do they have available, allowing them to be a part of that thinking and creation process is so important because already there's a huge amount of uncertainty that's out there that also creates a diminished capacity in our brains because our brains really like to be able to predict. We like to. And it's an important way of how we think and how we create a lot of efficiency and effectiveness is by being able to predict based upon past experience. If A happens, then B is an appropriate response and is going to give us a desirable outcome of C. Right now we don't have prior experience that that we can work with in these circumstances. And so our prediction factors are greatly diminished. So we we have to go into sort of a hyper agile state of asking important questions, trying small things out, running small experiments and iterations, getting the feedback, see how that goes, and then recalibrating and going out and trying again the next day. That also requires a lot more energy. But that's a little bit of it, especially in the first month. That was the most important thing for teams to be doing, was really trying small experiments, trying, you know, how are we going to work together remotely? What works, what times, what platforms, how can we connect, trying all of those experiments, seeing which ones worked while seeing which ones equally failed and then going out and trying again the next day was really important. And so creating structure from nothing was really one of the first and most important things that that was needed to. Then you create a place of stability where you have just a little bit more predictability and you can build from there. But there are teeny tiny steps. And especially when we're used to having a certain amount of flow in our teams. Again, we're trying to predict that. Or if we meet with these people at these times, we'll be able to get these kinds of results when everything you know, it's like the you're playing a poker game and the card table has been turned over and all of the cards are up in the air. You don't know you don't know where they're going to fall. So it's really hard to. Which actions to take? You just have to try different things. That's hard. But you there is learning in that and you are making progress. So value that and spend time with it and focus on that rather than the frustration of how things used to be or what it is that you're trying to predict.
Remote Working Webinars - COVID & Broadcasting
"You work in broadcasting, so everything must be great for you! All anyone can do now is what T.V." Not true! Bradley Wilkins interviewed Ajey Anand at Norigin Media, and in our first installment, they're discussing the immediate impacts of the Coronavirus on the Broadcasting industry both in Norway, and globally. Stay tuned for further installments later this week where Bradley and Ajey discuss: The future of broadcasting How Ajey is keeping morale high in his team The importance of marketing & communication, now more than ever. FULL TRANSCRIPTION: Brad Wilkins: I'm Bradley from Darwin Recruitment. I'm having a webinar conversation with one of my friends, Ajey from Norigin Media, and we're going to be discussing the current effects of the current climate on the media industry and broadcasting, to be exact. A So, yeah, I'll let Ajey himself and the guys at Norigin. Ajey Anand: Yeah, I'm gonna do a wave because we're learning how to be more virtual today. We're a Norwegian company and we've been in the TV technology space for over a decade. Nearly two, I would say. We're already in 2020 and the TV technology part of things that Norigin does is everything around streaming from the video aspect to posting. We've been hosting video services since 2004. We do a lot of UI/UX development; both services and products. So we've we're a Norwegian TV technology company and streaming has kept us Brad Wilkins Well, the quick adjustment that everyone's had to make, obviously to the coronavirus situation. How much of this has actually had an impact on the broadcasting and the media industry? Ajey Anand: Today, at the moment, I think specifically on the broadcasting and streaming industry, I hear from a lot of personal friends that 'it must be going good'. It's definitely not. I think, being a part of the industry, that the quick two things that comes to my mind is production has been halted, which requires people to be a part of it. Social distancing basically does not allow production to go on, whether it be actors on soap or whether it be sports in general, which requires content to be created in terms of what one needs, for life content or new content to be producing the series, etc. has been halted completely. And you can see new shows coming up, not just during this period, but the year that follows it as well. Advertisers who spend all of their budgets, or most of their budgets, on TV and digital formats have not just stopped because there is no new content, but there is no commodity and services to be sold because people are staying home and limiting themselves to the absolute basic needs, which is, you know, food, water, shelter You don't need to buy anything. And advertisers normally advertise what's what's being sold on an absolute current need of commodity sales. And if there is nothing being bought, there's nothing to be sold. Of course, we'll see a lot of brand recognition, which is a small part of the budgets which we'll see going on. But the money being invested in the industry has slowed down because of lack of content, new content and lack of sports and lack of advertisers which will which will trickle down across the industry, whether it be at innovation, youth development, launch of new services. People will rely on existing things in the market, including existing and old content. And that's what's being streamed right now. Brad Wilkins: Yeah, so how is that obviously had a knock-on effect to you guys, to your services or how you guys are adjusting? Ajey Anand: I think a couple of things. I think the whole company working from home has had an effect, but I think it's relatively extremely positive. I've yet to see the larger negative side to it. Personally, at least. I'm not going to brush it aside, though. Of course, I've heard and read the news and seen a lot of people being affected by it. But from from our company perspective, I think we sort of work from home. I personally started working from home rather early because of my own travel quarantine. The company started a bit earlier than the rest of Norway was asked to simply because we thought it was a good and quick move to do it. Having been working from home, I think our staff, our colleagues have seemingly become more efficient. I don't have any reports to it. It's just a feeling at this point in time we are putting down some numbers to see how efficiency is better. Quality seems to be better. People seem to be making use of their time a bit better than before, I guess. I don't think it's a very good thing because they're clearly working much more, I think. And of course, where we're relying on this time so that people can can improve the quality of their lives at home as well, which, you know, affects the company. And I think I'm waiting to see that to be converted, to be seen tangibly, financially. I think a lot of companies have been hit hard on the consultancy side. New development services are being slowed where we're only seeing absolute urgent needs, but we're not seeing any preferences or things that they want in the future. There's no huge advancements in going and going on the advertisers are not spending, like I said before, which would mean that innovation is coming down a little bit.Add Speaker00:05:44.510But I think it's a bit early. It's been a couple of months. So it's it's initially at least, it's affecting the company and the morale, I would say, on average, in a better and positive way.
Remote Working Webinars - Coronavirus Crisis Creates Opportunity in Robotics
"Crisis creates opportunity!" The Coronavirus crisis has, in some ways, required us to push 'fast forward' on the deployment of a wide range of robotic solutions to the problems the world is facing today. In our second installment from Lewis Adams-Dunstan and Rian Whitton, Senior Analyst at ABI Research, we discuss the huge opportunities on the horizon for the Robotics Industry and Industrial robotics in general. As insightful as the first installment, Rian's expert opinion really opened our eyes to the positive changes in the industry, despite the global crisis, and the opportunity for the robotics experts of the future. Click below for the full video: Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION Lewis Adams Dunstan: Is there anyone that you obviously say that's been positively affected by this? I mean, no one's been positively affected, but from a business perspective, being able to actually benefit from from how things are moving forward.# Rian Whitton: Yeah, absolutely. And this is probably the most interesting thing about COVID, 19. I mean, the economic response, the public response. It's on a scale that we haven't really seen, arguably since World War Two. We're looking at the level of nations and the private business. And, you know, crisis does create opportunities for things that were previously impossible to take place quite quickly. This isn't robotics. But if you look at telehealth and just sort of, you know, 10 operations in the health sector or just digitization of the workplace. I mean, in a sense, you might think that COVID, 19, might put a lot of CTO is in digital transformation veeps out of jobs because it's managed to basically change the way we work in a matter of weeks whereby previously CEOs were giving like roadmaps for five to 10 years. So it's definitely changing very quickly. I think if we're going to look at the robotics companies and the robotics applications that are going to benefit for them, COVID 19 and the response to it. There's the immediate public response to COVID 19. And then there's the broider kind of economic impact. I think if you look at the first order effect, if you look at the health response, you see robots that have been equipped with ultraviolet light, which basically go round to a hospital and basically use UV lights to disinfect the facility. About 99.9% of germs. And obviously, in the case of COVID, you have massive pressure put on hospitals and you have, you know, a major problem that generally when hospitals get busy, the infection rate at doctors can very often skyrocket And that often leads to a lot of extra stuff that's unnecessary deaths. So the fact that these robots were there and they were only hope to market quite recently, it is really a sign of sort of the industry, sort of, you know, ingenuity and success then these systems. About 2000 of them have been ordered from Denmark. That's 2000. So it's quite expensive to ship to China. There are about 19000 rate hospitals globally. So I think they began to increase their installed base and become from suddenly every news agency to quite ubiquitous in a very short space. You then have other applications like decontamination robots that spread hydrogen peroxide on train from public transport. They're being tested at an increased rate disinfection being delivered by a drone in places like Wuhan. And then, you know, if you're on the scene of cleaning and maintenance, there's actually will try to hope it was a big increase in the number of robots used to do floor scrubbing in retail stores. Lewis Adams Dunstan: Yeah, I've seen loads.Add Speaker Rian Whitton: Yes, right. Yeah, absolutely. And it's it's pretty much the norm. I mean, you know, we're talking about thousands considerably faster growing than the self-driving car space or robots in any public setting. And they're actually because know covered is obviously creating a lot of anxiety and a big part of a retailer's job, especially in brick and mortar retail, is to, you know, actually make cleaning a much higher priority to, you know, document it to make sure that it's, you know, you know, rigorous, to make sure that it meets all necessary standards. And the robot, not far from just alleviating the labor shortage or just being convenient, actually collects a lot of data, which is then used to monitor the cleanliness of the store. And so, you know, those applications are going to increase as well. Yeah. So that's cleaning maintenance. Then you also have robots for material handling. Lost mile delivery is obviously some you know, it's a part of the supply chain where the additional costs are very high.Add Speaker00:04:39.030And so tech companies are focusing very heavily on reducing costs. One potential way to do that is through automation. And you've seen, you know, companies like Starship Technologies, they've set up in Milton Keynes in the U.K. It's a very kind of línea, you know, easy city to direct a robot to build an automation system around. They already have, you know, an operation there where about 1800 people are served by these robots and about some people might use that robot for delivery if, you know, groceries, pizza, 200 times a year. And that's being expanded to encompass medical supply. I mean, you've got Chinese logistics giants doing that in Wuhan. You've got autonomous shuttles delivering medical supplies to clinics in Florida. You've got neuro doing grocery testing in California. So and this is part of COVID 19.It has, you know, opened up a lot of public space whereby, you know, robot pilot testing now is considerably easier. And the question is when and if everything goes back to normal and these operations are still going on, if they are sufficiently safe, it's not like you're just gonna be able to turn the clock back on them. They will in some form or another, still be there. Lewis Adams Dunstan Should they will be worried then that, you know, post COVID 19, that they're not working right now. If this does work and they are really efficient, that you might have the ratio or those jobs that were available to you before might well be available Rian Whitton: Yeah, I mean, look at the question of robots taking away jobs. There's a lot of conflicting literature on it. I mean, my personal view is that if you tend to we tend to look at the periods where employment growth the most, it generally is those periods where productivity increases the most. Companies that see productivity increases because they've deploy capital equipment and robots and automation tend to be much more eager to hire than those that don't invest in capital equipment and rely on on very cheap labor. So I would not be particularly worried about last mile delivery vehicles taking away jobs. A lot of this is not necessarily ready to be commercialized at mass scale. You're still going to negotiate. It's considerably more difficult to operate these systems and people tend to give credit Yeah. So a bit. I mean, obviously, a lot of people in the leisure industry find themselves unemployed at the moment. I think about 16 million workers in the US filed for unemployment as of now. A large number of those jobs will bounce back and be covered. And, you know, we've gotta remember the scale of the robot deployments. We're talking at most hundreds, maybe into the thousands. But this is not going to be, you know, millions of shipments, you know, at this point. You are very nice and stage development. But I think you also add another big application is intelligence monitoring and surveillance. Thermal cameras have skyrocketed in shipments, primarily because they're useful for detecting temperature and work. Companies are using it to monitor their workers. And very often these are being deployed on drones or in robotic vehicles. Drones are also being equipped with loudspeakers to give instructions to the populace. I mean, about a quarter of the world's population is now under quarantine and lockdown So keeping tabs on that monitoring that is is obviously a very big job.
Remote Working Webinars - The Importance of Overcommunication and Processes
How do you counteract the lack of human contant? How do you combat the absence of office chat and conversation? Richard Straub talks to Fabian Richter, Director of Engineering about how he has tackled these issues at Cape Anaytics. Over-communication Well planning processes Good sprint planning Good quality planning OKRs for goal setting Be clear and explicit Document everything Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Richard Straub Hi, guys. Richard here from Darwin. I'm joined today with Fabian Richter, Director of Engineering from Cape Analytics. Welcome. Cape Analytics uses A.I. and geospatial imagery to provide instant property intelligence, for example, for insurance companies;hey make the insurance process more frictionless and more accurate. Today, we talk a little bit more about the effects from the pandemic at Cape. And what the have done with the hiring process and and also the remote working. Thank you again for joining us. What I would like to know is how Cape Analytics has been impacted by the pandemic. Is there anything challenging still now? After a couple weeks off 100% Home Office? Fabian Richter In many regards, I think so. On the one hand, what's really much more challenging is just to to uphold effective communication. So what, you don't have is the situational awareness that you usually have when you're in the same room with a person. So, if you're forced to use slack, then you don't get immediate responses. So, that may be a challenge. So, you know, you're answers are trickling in over the course of minutes or hours, depending on how busy the other person is. You can't just walk out to the person's desk and poke him for the information that you want. And then, taking away too much context, I think, there's a lot of things that happen in between that you have some some sense of office awareness. You just passively listen to a conversation that two people have in the office, which obviously, if you take it to a specific dedicated one to one conversation on slack or on Zoom, you don't have that opportunity. So it's now, more so than ever, important that you give the context that's necessary for the people to understand where you're coming from. So if you decline a meeting, explain why you do that. If you finish a deliverable, that other people will just passively absorb that information. Go ahead and tell your team on Slack. Richard Straub Right. So that people do know about that. And make sure that you over-communicate things. Fabian Richter: So as a manager, you want to explain your thoughts more cautiously, your assumptions and what you expect people to do and maybe consider providing both feedback and verbal and in written form. So just to make it more explicit. Richard Straub: All right, so overcommunication is one of the things which is important. Do you have other tips how to be engaged or how to make it as clear as possible in remote collaboration? Fabian Richter: I think it's super important that you try to step up your game on processes that you have in place. So ideally, I as a manager, if I disappear overnight for two weeks and I come back, I would still want to see things making progress even without me And if that experiment were successful, I would attribute that to good processes that we have in place. So by that, I mean good srint planning, good quality planning. OKRs for goal setting so that people have an idea of what the next three months are going tobe about. So, make these things explicit and try to document that more so than before. And just working toward that is really critical. Richard Straub: All right, clear. Lastly, do you have any tips to say to stay fit and in shape during this at times? Fabian Richter: I wish I had an answer that I mean, I think I have the answer, I just need to start living up to it. I mean, at least in Germany, you're allowed to go out for physical exercise . Now, the bar is actually much lower than before because I don't have to commute. But I'm not I'm not figuring out how I can go for a run on a daily basis, which I totally should do. So I guess my try to stick to daily habits so I'd get ready for work, get dressed up, don't sit there in your pyjamas.Stick to a rhythm that you always had. Try to keep things as normal as possible and then try to stay in good physical shape. Richard Straub: All right. I've got some good tips for for the audience. I have a structure and keep it normal. Thank you. Thank you so much for all the people you want to know more about Cape Analytics or want to know more how Fabian comes through these times, leave a comment below or contact us directly and then we get in touch with you.
Remote Working Webinar - "It's not normal, don't manage like it is"
"It's not a normal situation, so don't manage your team like it is." We all have team members that are working remotely whilst also trying to home school children or care for family members. So is it fair that we expect the same level of output from them? In our second installment from Delivery Hero, Eden Whitcomb talks to Raz Shuty, Director of Engineering about managing skilled teams remotely, and how it's imperative to not manage as if it's 'business as usual.' How have you adapted your managerial approach? We'd love to hear from you. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact:# Form ID:5465 Eden Whitcomb: Welcome and thanks for joining us. You're here today as you believe that information and knowledge sharing is critical in a connected world. Our goal with the show and company is to introduce high quality actionable insights that will help hiring managers and job seekers to execute lean recruitment processes and gain industry knowledge that further enhance their careers. Today, I'm joined by a highly skilled manager and the co-founder and co-host of Tech Point Charlie, a multifaceted technology and culture podcast. For the past six months he's managed the demand and logistics team at one of the world's largest food delivery and distribution platforms. Prior to this, he's been the CTO and manager to a number of different organizations and teams throughout Berlin. It's my pleasure to introduce Raz Shuty, director of engineering at delivery here. Raz Shutyt: Really happy to be here. Eden Whitcomb: With your situation in particular, what I'm keen to understand is, the work life balance. You know, I know you have a young family and I'm not in the boat of having to deal with young children and work. So I'm hoping you can shed some light. How have you managed to keep your your children or child entertained whilst having to still manage and do your job Raz Shuty: I mean, it's very tricky to an impossible task like the sitting game where you run around and you have less and less chairs, right. It's the same concept where you have a kid and you have time and always more things pile up and you just need to find a place to drop something. And at the end of the day, we as society need to realize that this is not a normal situation. We cannot expect more productivity from one another. And we can't expect that, not just for parents, but for everyone. I think a lot of the discussions that I read recently about how managers should cut slack for parents, but actually, I would say, managers should cut slack for everyone. Yeah, basically you don't know. Even if someone doesn't have a child, maybe they're taking care of an elderly person. Maybe. Maybe they're just struggling to be alone. So it's not a normal situation. It's better that we all think about it as a temporary, unnormal situation. It's not business as usual. It's just it is what it is. And as long as people do their best, that's that's what matters.
Remote Working Webinar - The Impact of COVID-19 on Autonomous Driving & Industrial Robotics
"One thing that this likely recession will bring into focus is the profitability of many robotics companies. Too many have relied so extensively on VCing corporate subsidies without actually finding a road to profitability. That's not just a problem with robotics. Many Silicon Valley companies are very exposed to a recession." In today's insightful installment of our webinar series, Lewis Adams-Dunstan speaks to Rian Whitton, Senior Analyst at ABI Research Rian has kindly given us his view on how COVID-19 will impact the automonous driving industry and industrial robotics in the short-term and his predictions of the positives impacts for the industry the future! Stay tuned for more more from Rian in the future. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Lewis Adams Dunstan: From where I sit as a recruiter, autonomous vehicles seemed to be something that popped up more or more certainly in Boston and San Francisco with COVID-19 in mind then how has that disrupted the robotics market and that upward curve you've mentioned that we were on? Ryan Whitton: So I think if you look at the autonomous vehicle space, I mean, for one thing, that market has some major questions it has to answer regardless of COVID-19 has enormous investment with virtually no revenue and no actual dedicated business model. A lot of the people developing this technology are in effect open to whoever can make a business model out of the technology they're providing. Another issue that they're coming into focus is the issue of improving their safety models. Now, the idea was that the safety models for navigation for autonomous vehicles on the road would match Moore's Law, that it would just exponentially increase. What's actually happened is that as the models have got more sophisticated, the edge cases have got harder to create and replicate and it's become much more expensive to develop. Better data that you can then feed into improved this model. So the actual costs with improving these systems has increased markedly. And already prior to COVID-19, there were casualties. COVID-19, basically suspended all testing of autonomous vehicles in California from the get-go because the vast majority of these vehicles still require a driver in the vehicle. There's only two companies that are registered to deploy completely driverless vehicles in California, Nuro and Waymo and they have continued testing, but most other companies had to suspend it. And at the same time, some companies like Starsky have gone out of business so that the self-driving car space, I think, is in a state of real, not peril, but flux. And there will be considerable casualties because one thing that this likely recession will bring into focus is the profitability of these robotics companies. And too many, I'm afraid, have significant investment and have relied so extensively on VCing corporate subsidies without actually finding a road to profitability. Now, that's not just a problem with robotics. That's also a problem with Uber, which we work. There are so many Silicon Valley companies that frankly very exposed to a recession. And they've they've largely been able to survive because of the sort of fair weather climate we've been in. And I think this recession is going to probably create some second order effects in the tech industry, which will see a lot of players burn quite severely. Now, moving on to industrial robotics, there is going to be a massive shortfall in the first half of the year. China is obviously the largest manufacturer in the world and it's got the largest single installed base of robots. The two major industries through the industrial robotics market are the automotive manufacturing space and electronics, including smartphone devices now in China. In Q1, I think the shortfall in automotive sales was about 80 percent. They're expecting about a 5 percent drop for the whole year.Add Speaker00:03:30.570And when it comes to electronic devices, as much as half of the revenue could be lost due to Kobe 19, even when and if China gets back online, which they say they are. When it comes to manufacturing capacity, they still have to deal with a much lower demand in the United States and in the developed world. So those two markets get greedy. And you will probably see a subsequent shortfall in industrial robotics sales, at least in the short term, in the long term. They probably have a much rosier future because all this money has just been thrown into the economy, either through fiscal stimulus or just through sheer liquidity to the point where CapEx and capital expenditures and capital equipment is very likely to increase in the long term. But yet there's no doubt that at least to a large segment of the robotics industry, COVID-19, has been incredibly disruptive. You know, for the first quarter, if you look at consumer robotics as well in their forecasts for their growth pattern for this year has been totally thrown out the window. We're talking about the consumer vacuums. But you know that that's the Short-Term. I think COVID-19 in the long term is going to be, you know, sort of counter-intuitively quite beneficial to the robotics industry and to the automation of, you know, various practices in general.
Remote Working Webinar - It's time to show TRUST
"There are a lot of complaints about how employers and managers don't know how to keep employees. I think this is a really good opportunity for companies to build really good relationships with employees. So that they see the benefit of staying" How do we all do that? TRUST! In today's installment, Eden Whitcomb talks to Raz Shuty Engineering Manager at Delivery Hero about the importance of lowering your expectations, showing understanding and, most importantly, demonstrating trust. It's a really great webinar that talks about how the way we manage now, could effect the overall retention of talented staff in the long term. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Eden Whitcomb: Welcome and thanks for joining us. You're here today as you believe that information and knowledge sharing is critical in a connected world. Our goal with this show and company is to introduce high quality actionable insights that will help hiring managers and job seekers execute lean recruitment processes and gain industry knowledge to further enhance their careers. Today, I'm joined by a highly skilled manager and the co-founder and co-host of TechPoint Charlie, a multifaceted technology and culture podcast. For the past six months he's ben managing the demand and logistics team at one of the world's largest food delivery and distribution platforms. Prior to this, he's been the CTO and manager to a number of different organizations and teams throughout Berlin. It's my pleasure to introduce Raz Shuty director of engineering at Delivery Hero. Welcome to the show. Raz. Raz Shuty: Really happy to be here. Eden Whitcomb: You've found a very nice balance between managing your workload and obviously being a parent still. I know a lot of people have struggled with that. So did you find that the parents in your team adopted it differently or are they still struggling with it? Have you guys openly discussed different ideas around that? How are the people around you coping? Raz Shuty: I would say that from the horror stories I've heard, people are actually fine ish. Doing fine ish is a very temporary solution and it's still not easy at all, but it's survivable. It really depends on how many kids you have. It depends on the situation with each one of them, like your spouse working or not. You have a spouse or not. Tip I would give us for organizations and managers; you have those really, really talented people. If you want them to stay. If you appreciate their work, then it's time for for you now to actually kinda lower your standards. Just be fine with it. Tell them that it's OK. Like re-assure your employees that you actually appreciate them. It's fine. It's a temporary situation. Try to help them as much as you can, wherever you can. Don't start to look at those employees now and say this person used to be a high performing developer and now he or she are not. Maybe I should do something about it. No, just I completely don't go that direction and go in another direction. Like trying to project to them. Do you actually value them and try to make them feel better? Honestly, I think this is a really good point in time for organizations and managers to kind of be the point where employees can actually lean on. This is the best point in time to build trust. We all talk about how employees churn all the time.Add Speaker00:02:42.700And there are a lot of complaints about how companies and managers don't know how to keep employees. I think this is an opportunity for companies and managers to build really good relationships with employees so that they will see the benefit of staying.
Remote Working Webinar - Leading Motivating and Inspiring
"Big objectives don't really change much. You always want to grow, you always want to have more users, you alway want to have more revenue. But the way you work towards this goal changes every quarter." So, how do you ensure that everyone is on the same page, and working towards your business goals during this challenging time? How do you motivate your teams? In our latest installment Eden Whitcomb speaks to Wouter Verhoog from HUMANOO about how he ensures his teams are working towards a common goal, not only when working from home, but in general. Watch the full video below. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION Eden Whitomb: You're here today as you believe that information and knowledge sharing is critical, in a connected world.The goal of this show and company is to introduce high quality, actionable insights that will help you execute a lean recruitment process from talent search through to onboarding and motivating your teams. So today I'm joined by an executive, former founder of Buddyguard, an advisor to multiple organizations across Berlin. His passion now lies in people and with his team. They're making people's lives a little healthier step by step. Their platform right now helps organizations to keep their employees healthy, happy and focused. And with their dedicated yoga, meditation, sporting and healthy eating programs, they do just that. I've had the pleasure of knowing this man for several years now. Please welcome. Wouter Verhoog, COO at Humanoo. The biggest thing, I guess, that I've identified is the celebration of success both for the individual and the team level. And getting people kind of really engaged for you and your team. How have you guys kind of managed that process in the past three weeks? Wouter Verhoog On Monday it's called Monday Focus from starting at 10:00 for usually about 30 minutes. We just do the biggest updates; What's going on this week? What do we want to achieve? So every team leader or department head usually comes up with his or her top two or three priorities for that week. And then by Friday, that is called Friday Wins. That is the moment where we just let loose. We open a beer now remotely. So we're just around 50 people on the screen saying cheers and raising their glasses and bottles. And we just go through the list of OKR results. Where are we? Did we move the needle in the right direction? Does anyone need any help? You know, it's just kind of the moment to create some healthy discord. And after that, it's it's time for every department to just say that one little thing that they won this week. Sometimes that is hiring the right person, sometimes you finally close that deal or maybe you haven't closed the deal, but you finally found that one special intro that you need for that company. And then if you work in R&D, you've finally solved that bug or you released a long wanted feature. There's always something positive that can be celebrated on a Friday. And so we start the week with focus and we end the week with a win. And it just feels really nice to have everyone onboard and have everyone on the call Eden Whitcomb: So with that win process and with 50 people on the screen at one time, does everyone get the opportunity to actually have their voice heard or it per department? Wouter Verhoog: It's per department. We start with the OKRs. We just go through the list. And for every key result, we have 1 to 2 owners and they will update everyone on what they've been doing. Maybe this week its owner A, next week it's owner B, or there's some exchange going on there So not everyone gets to have their say because in the end, then be looking at a three hour session and then for the wins, it's just the department heads. Eden Whitcomb: So are you guys still incentivizing your teams? Are the managers or the team leaders responsible for that process.? How does that work on a success level? Wouter Verhoog: OK, so if there was anything that we could incentivize people with or make them a bit more focused and in the end, a bit more of a happy employee. It was making sure that we eliminated the white noise between departments as much as we could. We're still looking at ways to incentivize the best ideas. For example, a hackathon that we're organizing this quarter, which will not be a tech hackathon, but across department hackathon. And then the best idea the winning idea, the inventors will be sent on a weekend away. Maybe to Paris or just somewhere really nice. You know, not an Amazon voucher. But in terms of OKRs, we didn't need any further incentivization because what was most important is getting the buy in from all the teams.And for everyone to know exactly 'what is my role, what is expected of me, how can I contribute to the bigger picture' that for us has been the most empowering move to make. And that is kind of the incentivization for now. Eden Whitcomb: So less of the short term wins and more of the long term motivation. You're part of something bigger. Wouter Verhoog: Exactly. The most thing with OKRs is 'we're here now. Where do we want to be at the end of this quarter?' You know, you need those those big objectives. They don't really change much. You always want to grow. You always want to have more users. You always want more revenue. You know, you have this basic set of metrics that are important, important for the growth and survival of your company. But the way you fulfill those goals, that changes every quarter.
Remote Working Webinar - The Impact of Coronavirus on a Startup Business
How do you review the impact of the virus on your business AND make the changes needed to survive in way that is REASSURING and MOTIVATING to your staff? Yep. It's tough.... We're sure this is a conundrum that every business is facing at the moment. In our latest installment, Daniel Butler discusses these problems with Teo Borschberg and Nicolas Perony from OTO Systems and, as always, their advice is insightful. How have you tackled these issues? We'd love to hear from you. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Daniel Butler What do you say would be the challenges you face as a business in terms of your day to day work with the team and the guys you have working for you? Teo Borschberg So, I mean, the challenge is to manage a lot of different inputs. There are some very heavy macro changes that impact how we have to operate inside out. So, of course, a diminishment of work. A change of priority and in a certain anxiety within the team. So it's managing the process of understanding the ecosystem and how it impacts us, resetting the right priorities to make sure that we go in the right direction, and then applying that to the team in a way that is, you know, reassuring in a way that is motivating, in a way that is not too disruptive. And of course, we've had to be extremely cost conscious. And so we've had to revise our plan in terms of expansion, in terms of team, in terms of where we spend money. And we've had to had some difficult conversation in terms of reducing costs as well, for sure. Nico Perony So to be concrete, these came about in a phase where we were in full commercialization and deployment mode. So we had put together a team to do business development to sell and deploy. And just as we were ramping this up, essentially, the whole crisis started and we've seen projects essentially being canceled, postponed all over. So it has required us to revise very seriously our ambitions and also fundraising prospects changed completely, so for a startup an the last stage of growth, It's it's a significant impairment. Daniel Butler Yeah, I see that. I think I've spoken to a couple of businesses quite recently who were at that stage of a funding round or looking for investment. And this, no doubt, couldn't have come at a worse time for everybody. But for small businesses who rely heavily on investment and on those vitally important funding rounds, it can be really negative. But yeah, I think it's, as we say, it's important to be flexible and how flexible you can be can often determine how how you're impacted by that for sure. So, yeah, I think it's a it's good that you guys have got that flexibility for certain
Remote Working Webinar - Will the Lockdown impact Diversity and Inclusion?
Will the lockdown allow us to work more sustainably in the future? Surely businesses will be able to improve diversity and inclusion moving forward? Will this widen the talent pool for everyone? Eden Whitcomb and Lisa Quatmann from INFARM tackle these topics in our latest webinar installment? What do you think? Will your business be working more flexibly in the future? Will this alter your target talent pool? We'd love to hear from you. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Eden Whitcomb You are here today as you believe the information and knowledge sharing is critical, in a connected world. Our goal with this show and company is to introduce high quality actually insights that will help you execute a lean recruitment process from talent search through to onboarding and motivating teams. Today, I'm joined by a versatile engineering manager with a background by Frontend and Backend development for a number of companies, both here in Berlin and in the States. She's currently working with an organization that combines highly efficient vertical farming with AI technologies and machine learning to offer an alternative food system that's resilient, transparent and affordable. Having watched her grow from a Fullstack developer many years ago to the impactful engineering manager she is today it's my pleasure to welcome Lisa Quatmann, Engineering Manager at INFARM. So welcome, Lisa. With everything happening right now and I know you guys are pretty ready for what was happening, but do you feel that everyone is probably going to go more remote after everything gets back to normal? Lisa Quatmann: I have no idea. I mean, I very much like working from home, but I also like the interaction with my colleagues. So I dont know if I can answer that for myself. But the good news is that they now have everything set up to work efficiently for remote, whereas a lot of companies didn't before. Yeah, and that's not just in tech. I mean, I think it's really easy for us to focus on Tech. But, you know, I have friends that don't work in tech and now they're working remotely. They never thought they would before. You know, and so it'll be really interesting to see how that plays out after this. Lisa Quatmann: You know, for us, it's it's part of our mission, sustainability. And also a remote worker is very helpful for diversity and inclusion, diversity in particular. It's easier if you have this sort of flexibility. I hope that a lot of companies will see that it's not just a nice to have thing. That it's something that can support their mission. Eden Whitcomb: It opens up, as you said, the diversity, inclusion aspect. It does mean that you can get the best talent for your projects or people who are really committed to it without having to have to move for work. You know, you don't have to physically be there. And you're actually right. I mean, I've always been a lover of the office. And personally, I am desperate to get back into the office. I like my space. I'm the same. I find that working from home, I work way more than than I ever did. Sorry, everyone, but from my side, you know, having the office is that that escape aspect where work is work, home is home. So I'm still trying to find that blend. But I think especially from what we're seeing as jobs, you're right, you know, companies, are now ready for it. And it will be interesting to see the demand from, you know, employees to probably go up for remote working. And the companies that think, you know what? We can do this. I think they'll be the ones that thrive more and get the better talent. So, I guess it's kind of interesting to see what happens. Lisa Quatmann: Yeah, well, I think they can't say that they can't do it anymore. For people who have children, who are caretakers, maybe of elderly parents or they're disabled. You know, that sort of thing. There's a lot of reasons why someone would want to work from home or would need a lot more flexibility. And if you can provide them with remote job, then it really opens up a lot more people that you can hire. Eden Whitcomb: I'll take my own team and you can talk about yours as well. I haven't seen a dip in performance, haven't seen a dip in motivation. I haven't seen any reason to believe that they're not doing better than what I was doing in the office, which has more distractions. I think, in the office, we do distract each other. So I do find that the activity is actually going up for us, which I wasn't expecting. So I don't if that's the same for what you've seen? Lisa Quatmann: There's a feeling out there that we're all in this together. A Eden Whitcomb: Yeah, well, Lisa, I really do appreciate you taking the time. So thank you so much. And you know, I'll speak to you soon.
Remote Working Webinar - Increased Governance of Communication
Believe it or not... There are teams across the globe who have actually become more productive because of the remote working situation we're all in. Employees have been calling for more flexibility in remote working options for years now. It seems like the vast majority of companies have been very reluctant to fully adopt it. Until they had to. Nikolija Stojmenovic knew that FastForward.ai was a company thriving in the remote working world...but how exactly? Dimitar Chukaliev, Product Manager at FastForward.ai outlined exactly where they've seen productivity improvements: Increased governance in communication. (Or everybody gets the same information at the same time). Watch Dimitar explain it in detail below Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION Nikolija Stojmenovikj If you could think about something that is really positive that you're getting out of this situation, what would that be? Dimitar Chukaliev I think that a pretty good increase productivity of the team is definitely one thing and increased communication between the two. Well, increased governance in communication. Before you might have a chat on the desk. Now you're not able to do that. So everything goes in the Slack channel. Everybody's aware of everything. So you don't need to sync up between people. Everybody's aware of everything just because everybody gets the same information. That was not something that I had done before because usually we would have our sync once a day and right now, everybody is in sync all the time. Nikolija Stojmenovikj All right. So you're saying that it's actually increasing the transparency and also making the agile teams even more agile? Just because we are we are basically online and everything is out there for people to understand and see. Dimitar Chukaliev Yeah, well, I'm not talking about just transparency I'm talking a little more about governance where everybody gets the same information at the same time.Add Speaker00:01:07.500We were transparent before, but we were transparent or our recap meetings or and our stand ups. Right now, everybody gets the same information at the same time, which makes things a little bit quicker and a bit more agile. You're right.
Remote Working Webinar - Discipline and Work Life Balance
"My biggest distraction, when working from home, is work!" Many managers and business owners may be worried about their staff being motivated when working from home, BUT what if the problem may be the inability to 'switch off' from work? In today's episode, Eden Whitcomb is joined by Lisa Quatmann, Engineering Manager at INFARM in Germany who discusses the importance of a good work/life balance during this period. Click on the video below to view this insighful episode. Stay tuned for future episodes featuring Lisa where she discusses her hopes for the future, following the pandemic, in terms of diversity and inclusion. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Eden Whitcomb: You're here today, as you believe that information and knowledge sharing is critical, in a connected world. Our goal with this show and as a company, is to introduce high quality actioable insights that will help you execute a lean recruitment process from talent search and through to onboarding and motivating teams. Today, I'm joined by a versatile engineering manager with a background in Frontend and Backend development for a number of companies, both here in Berlin and in the States. She's currently working with an organization that combines highly efficient vertical farming with I.T. technologies and machine learning to offer an alternative food system that's resilient, transparent and affordable. Having watched her grow from a Full Stack Developer many years ago to the impactful engineering manager that she is today, it's my pleasure to welcome Lisa Quatmann at Infarm . Welcome, Lisa. So I guess working remotely, do you have any distractions that maybe you didn't anticipate when going through the motions, maybe less for you as you're used to it, but has anything crept up that you didn't anticipate? Lisa Quatmann: The one thing that I thought I didn't anticipate was that I would be distracted by work, especially whenever you really like your job.Add Speaker It's very tempting to just do one more thing. You know, it just snowballs. And the next thing you know, it's really late and you're still sitting at your desk. And it takes a lot of discipline to maintain that work-life balance when you're not commuting. We have a coffee break meeting thing. And you have to also say goodbye to your colleagues at the end of the day and close the laptop and walk away. Eden Whitcomb: Did you find that you work a lot more than when you was in the office? Lisa Quatmann: Well, at first, but yeah, you just have to have some discipline about it. That's all. You have to know when you're supposed to walk away. And it helps to have that space. You know, I don't sit on my couch ndt work. I have a desk. And when I'm not at the desk, I'm not working. Eden Whitcomb: The qualities and skills that somebody need, those you've already mentioned discipline and having the awareness of take a step away from the desk, stop working. What others you think people would need to develop either in themselves or as a team to make a success of remote working Lisa Quatmann: You have to be super organized. I start every day with a to-do list of only what I want to get done that day and what I need to accomplish. And any meetings that I have to prepare for. And I stick to that. That's it. If there's something else that comes up, I put it in a backlog. It's not very much different than when I was a developer, you know, you have your your backlog of tasks that you can do later. But I think, not just personally, but as a team, you have to develop really good communication skills. You have to reduce the number of meetings as so that people aren't sittiing all day in front of a screen. You use synchronised communication, so that you can collaborate on things. If someone needs to step out and watch their kids or walk the dog or whatever, then they can do that if if they don't have back to back meetings all day. And I think it's also really important to communicate with each other, like when you're at lunch, when you're not at your desk, when you're available, when you're not.
Remote Working Webinar - Tips for Onboarding Remotely
"So we know that we can work remotely, but how do you onboard remotely?" This is a question that we've been asked a lot lately and one that Megan McGuirk asks Carlo Fässler, Head of Tech Operations Capture Media AG. We're still actively recruiting for them and they say that it's harder for the onboardee that the company, but it's relatively easy to onboard a developer. Watch the full video below: Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCRIPTION: Megan McGuirk: Well, you're still hiring at Capture Media and we're working quite closely on that role. It's a big question that companies have right now as people can work from home but how do you bring someone into the team remotely? I know you've done it recently. So how are you onboarding people fully remote? Carlo Fässler: We actually started onboarding a developer just before we went into lockdown. But he actually had to go into quarantine earlier because he just travelled from Italy. So we decided to start onboarding with him remotely, even though we were still in the office. Then a few days later, we went into a partial home office. But basically once his quarantine was finished and we came to work, he only had a few days. And then we went into a into a lockdown and started the home office first 50% and then 100% just a few days later. So, yes, he's been working with us for almost a month now and we've only seen him face to face, maybe one or two days. So, I think generally it's harder for the for the for the onboardee rather than the person doing the onboarding. It's it's not a problem to onboard a developer if you have all the tools that you that you need to com,municate with them all the slack and to screen shares, etc. The only problem I see abit, is aunless you were in a video call, you miss the non-verbal communication. I mean, if somebody sits next to me and I explain something, I can judge by his face if he understood it or not and you miss that part in the onboarding remotely. Other than that, I think it works pretty well so far. I'm surprised, it's actually quite good. Megan McGuirk And how do you think he will settle in when he does finally come into the office and get to be one of the team, full time? Do you think it'll be a smooth transition from this remote onboarding or do you think you'll have to go through some things again? Carlo Fässler Well, we might have to break him in over a couple of beers, because what you can't do remotely is the whole company culture. He would probably have to get adjusted to the people again in a different way, because it's different, obviously. than when you meet in person, but I don't see any problems, it should be should be fine.
Remote Working Webinar - Using this time to Adapt & Evolve
It's a tough time for everyone, but how can you use this time to adapt and evolve your business? In the latest edition of our remote working webinar, we're joined by Teo Borschberg, who is based in Lisbon and Nicolas Perony (Zurich). Teo and Nico are the CEO and CTO of OTO Systems. They've kindly shared their experiences of how the last few weeks and months have effected their business. Teo & Nicolas offer some fantastic insights on how they've used this time at OTO to take a step back and to review, adapt and evolve. Click on the video below to hear more. Stay tuned as we have some more really insightful editions to come featuring these guys. Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 FULL TRANSCIPTION: Daniel Butler: Hi, guys, it's Daniel Butler here from Darwin. I'm joined today by Tio and Nico from OTO Systems. Tio is joining us from Lisbon. Nico is joining us from Zurich. And we're going to discuss the impact of the current situation over the past couple of months and the next few months, on a business and a start up and what that kind of things that includes. So. to start off guys, how has OTO been impacted by the last month or two? Teo Borschberg: The impact has been significant in a sense that most of our customers have been in Europe and our customers, our call center operators and the call centers have been closed completely for six to eight weeks. So that's a good portion of our customers that have actually completely shut down and everything's on pause until further notice. And so for the old business of OTO, in some sense, there's definitely a big impact by the Corona. Nico Perony: Not everything is as bad, of course. And when you stop running, you'll have more time to look around and think. And actually this came, in a time when we were thinking of broadening the scope of possible applications for our technology, and it has led us to actually talk to a lot more people and think of how to apply our technology much more broadly, including on very tangible applications or very tangible solutions for the current crisis. Teo Borschberg: If I can add to that also is exactly what Nico says. It's true where we are active in voice and even though call centers have closed, the voice sector is exploding because of what we just discussed, Daniel, right? The broadcasting market, the Zoom, the remote, the education, all of that has been exploding and voice and video are the center of that. And that consideration to open our technology to this market has been accelerated by the COVID. And so, despite having some negative impact, there is a tremendous opportunity at the end of the tunnel. Daniel Butler: And we're seeing a large number of businesses, globally, who have adjusted their business model and provide slightly different services using the facilities and the technology to have at their disposal, which has been great. So it's one of the great things about humans is that we adjust very, very quickly and everyone's pulling together really to kind of make make the best of the situation and to help out wherever possible. So that's really good and something that is essential for businesses and especially for smaller companies that have that flexibility, no doubt.
Remote Working Webinar - Finding the Opportunity in a Crisis
'Find the opportunity!' One of the mottos at OTO Systems is 'Behind every obstacle is an opportunity.' In today's insightful installment of our daily webinars, we're with Teo Borschberg and Nicolas Perony again. This time, they're offering their advice on the actions a start up should take in the face of a criss such as this: Understand your own business. Analyse how it is being impacted Don't be overly optimistic Be cash conscious Cut costs everywhere AND... FIND THE OPPORTUNITY! Do you have any advice that you'd like to share? We'd love to hear from you. Comment below.Write something here... Are you in need of assistance during this difficult time? Maybe you're looking to hire remotely, or are seeking a new opportunity. Or maybe you just want some impartial advice. Complete the form below and one of our speclialists will be in contact: Form ID:5465 Full transcription below: Danny Butler: I think one thing I was gonna ask you guys is as a as a start-up, as a small business. What tips would you give to other startups on how to how to get through this, ultimately? Teo Borschberg: First of all, I think it's important to listen to what's out there, but to be critical about what is once the situation within its own four walls. Right. Because there's a lot of tips that go out there and cut your cost and do this and do that. But it's important to analyse how this is impacting the company itself. Some might be on the rise. Some might be very close to a new city. Some may be truly in the shit so to speak. Teo Borschberg: So, to say, it's important to have a good analysis of how it's impacted the company first and then and then act accordingly. What I can just say is that prepare for the worst. Don't be optimistic but be realistic of how that impacts the company. Nico Perony: Everyone is an expert, and everyone has a prediction about the future and the last that long, etc. it will be three quarters, it will be two years. What I see is that we entering we're entering a new time, a time of very high uncertainty. The way I see it, if you look back on the last two big downturns, I think they were affecting less of the world than now. So it might actually be worse. And of course, I don't know, but I like to say it is good to prepare for the worst. Nico Perony: And one thing is very likely is that it going to get worse before it gets better. So, for start-ups out there, be very, very cash conscious. Try to cut costs everywhere. Absolutely. Consider an investment landscape where it would be very hard, nigh impossible, to raise money for the foreseeable future. So, think of different strategies and find the opportunity. I think, at OTO, one of our main values or messages is that, always, behind every obstacle, there's an opportunity. Danny Butler: So, everyone has to be hard at work on finding the opportunity. I think it's a very applicable to the work that I do as well, in finding the opportunity. It can be harder to find at these times, but no doubt definitely more rewarding when you do find it. So, no, I definitely think it's a valuable information as well. Teo Borschberg: How has your work been impacted by the virus? Danny Butler: So, one thing very similar to what you explained is we've got a number of businesses whose industry has been massively affected and impacted. So, for example, I work with some consultancies and very early on in the process, we realized that they were not able to travel to customer sites. Now, sometimes this work can be done from home, but sometimes this has real impact. And it means that some businesses have said, "well, let's put this on hold now indefinitely", which, I see, for recruitment purposes is not great, but we're all in the same situation. Danny Butler: I think the main thing with this current topic is that we're all in the same boat. I often think in life that things are more difficult to accept if it's happening to you and nobody else. But we're all in the same situation. Everyone's interests, everyone's industry, everyone's business is being impacted. But yet, recruitment is being impacted in a big way. But, because of technology, we are able to conclude some processes still. And there are many businesses who are very open to concluding processes via video calls and even onboarding people during this time remotely. So, you said how businesses have to be willing to adapt. And I think one thing we're seeing now is that people are becoming a bit more open to the idea of working from home or working remotely. So, they're going to be willing to onboard somebody remotely, which is something that probably felt extremely alien a little while ago. So, in that respect, I think longer term that will help with recruitment and that will be something that's a welcome addition. Nico Perony: But yeah, no doubt these are tough times and many businesses potentially could even go under. We've seen that with a few already. And yes, sadly, that's inevitable. I think like you say, it's important for people to really kind of assess things almost day by day and be willing to show flexibility and make those adjustments that mean that they can they can stand every chance possible. All right. Some businesses will go under. Some companies will die. And that's it, and those that survive will emerge from this stronger and more resilient. Yep. Danny Butler: Yep, I definitely agree. And I think that's the message that we've been told here at Darwin. And I think the message that a lot of people were kind of putting out there is, yeah, these are tough times, but at the end of it, I want to be in a better position and massively learn from it as well. I think that's what's the important thing; to take pride, I suppose, from the way everyone's dealt with it in terms of business and personally. Danny Butler: So yeah, one thing, Nico, is when I when I come across the office earlier in the year, we agreed that I would come over in the summer and that we'd have a barbecue and go swimming in the river. And I'll make a pact now that whenever I can come, I'm still going to go swimming in the river. So even if it's in the winter time, I'm going to do it. Nico Perony: Well, I went swimming yesterday. It is seven degrees Celsius. And it is getting warmer. Invitation is still on. And we'd love to have you. Danny Butler: Take care, guys. Keep up the good work. And I'll speak to you again soon. They say a lot about.
Top tips for onboarding remote employees.
It's a worrying time for everyone at the moment; the growth of the outbreak is more terrifying than (i think) any of us expected and it's affecting the majority of businesses in many different ways. BUT, not every company can afford to completely halt their hiring plans. In these uncertain times, certain roles are essential to sustaining and growing a business and, for some industries, hiring is essential right now. Onboarding a new employee is important for any business and in normal circumstances a priority would be placed on ensuring the first impressions of a working environment are high, and all the required information can be delivered to a new employee through a series of face to face meetings. But, unfortuntely, that isn't possible for the vast majority of businesses at present. If you’re continuing with hiring plans right now, here are 10 tips to consider when you're building your remote onboarding process. 1. Ensure your new remote employee can easily complete his/her HR paperwork: Do you have an e-signature tool in place? Completing contracts and other paperwork can be frustrating and time consuming if they need to be printed, signed, scanned and returned. E-signature tools such as HelloSign or DocuSign, are easily to use and cost effective. Employees can add their signatures digitally and share contracts with you in a secure environment. 2. Ensure your new remote worker has the hardware and instructions they need to get started. Do you have a complete checklist of everything a remote new starter needs to get started? You must ensure that all hardware is ordered well ahead of their start date and that your remote worker has received everything in time. Make sure that your IT department has introduced themselves to offer any needed assistance. You should ensure that all remote workers are familiar with: • Computer security procedures. • File-sharing applications/folders and any cloud backup software that is used in your business (like Google Drive,Dropbox etc). • Password management and data encryption tools to protect their devices. 3. Does your remote worker understand how to communicate to your business? Provide clear instructions on how to contact team members and troubleshoot communication technology. Provide clear instructions on how to access/set up: • Company email • Group messaging tools • Video conference software • Webphone application 4. Create a remote worker starter kit. Help your new hires feel part of the team by sending them a personalised starter kit. This will go a long way in making them feel welcome. You could include: • Branded merchandise; water/gym bottles are always well received. • A welcome letter or note from their team/manager/CEO. • What do you know about your new starter? You could you include a thoughtful gift such a gift voucher to an online store. 5. Ensure your remote worker feels part of the business - from day one. Even though they’re not going to be in the office, remote employees play a part in your team culture. Here are some ways that you can help them feel part of the business from day one: • Video content is a great way to give a remote worker a feel for their colleagues. You can use free tools such Loom to create short videos of team members talking about their role in the company, hobbies etc. • Do you have any footage of recent gatherings or company meetings? • Do you have copies of any presentations delivered by the leaders of your business? • Do you have any literature on your company values? 6. Arrange a face-to-face meeting (as soon as it is safe to do so). The below tip isn't relevant in the current climate, but could be considered if you continue to remotely onboard staff, once everything is back to normal. Is your remote worker based near your office? If so, consider having them work from your offices during their first week. If they’re not based locally, try to invite them on-site as soon as possible, so that can meet their team members in-person. If you have a large number of remote workers, try to schedule quarterly or annual events to give everyone the chance to meet. 7. Prompt hiring managers to set clear goals and expectation from the outset. It’s difficult for remote workers to work effectively if they have to wait for their manager to call or email to learn what their next steps are. Make sure hiring managers: • Develop and share a task/project calendar after new hires’ training and onboarding sessions. • Define short-term and long-term goals and objectives. • Schedule regular one-on-one catchups to discuss upcoming projects, progress and to resolve any potential issues. • Share the overall projects of the team and give regular project status updates. 8. During week one: Set up virtual meetings with team members and other key employees. These meetings could be one-on-one and/or group calls. During their first days, remote employees should meet with: • Their team members. • Their manager and direct reports • Relevant employees from other departments 9. During month one: Arrange all necessary training. It can be challenging to train remote employees but with a wide range of online communication tools at our fingertips, it’s easier now than it ever has been. Any delays to training your new remote worker may leave them feeling demotivated and undervalued. Ensure that the trainer follows up each session to answer any potential questions. COMMUNICATION IS KEY! COMMUNICATE REGULARLY WITH YOUR REMOTE WORKER You need to know if they're facing any difficulties and whether they've settled into their new role, so you can react accordingly.
How To Hold Online Coding Interviews Using Zoom
Interviewing somebody across the world has never been easier. There are a whole host of services you can use to conduct a remote interview. Skype, Zoom, Facebook and even WhatsApp all have built-in video calling features. Although, there is a catch. These can sometimes fall short for certain types of interviews. And especially for interviews where work needs to be discussed and talked through. A great example of this is demonstrating coding abilities. This simply cannot be done effectively over a typical video call. But, there are services out there to help with this exact situation. Read below to find out. Zoom has a huge amount of functionality for FREE. There are plenty of tools on the market will allow candidates to demonstrate their coding abilities. But, we have the most experience with Zoom AND it has the added benefit of offering a large amount of functionality for free. So far, so good. Setting up an interview using Zoom is easy, but there are a few settings you need to configure to get the best out of it. Read our other article here to find out the 5 crucial Zoom settings to you need to set up. So why is Zoom so good for coding interviews? It's simple. Zoom allows for screen sharing on desktop, tablet and mobile devices. The host AND the interviewee can screen share by clicking on the Share Screen icon. It's so simple to use. And even better: The host doesn't even need to pass the control of the interview (or make someone else the presenter) to allow the interviewee share. But wait, there's more. After selecting "Share Screen" located in your in-meeting toolbar. You can choose to share your "Desktop" or an "individual application/window". You can access additional screen sharing tools using the meeting toolbar: These include: Pausing the current screen share Sharing a new window Annotating your current screen share (using a pointer or drawing tool) Remote control; the interviewee can allow the interviewer to control his/her keyboard and mouse. Additional tips for conducting a successful remote interview 1. Pick a solid platform. None of completely full proof but tools such a Zoom and Skype will be the most reliable. 2. Video calls only! It's very easy to be distracted on a regular 'audio' call. Video meetings require singular and focussed attention. 3. Test the connection before the call. It might be best, where possible, to use a hard line rather than wifi. 4. Plan your space. As well as testing the connection, ensure that you've checked your 'interview space' before the call. Check the camera angles and distance, ensure your space is tidy and make sure you don't have any light casting shadows over your face. 5. Use headphones with an external microphone. This will capture the best quality audio (microphones on laptops are never good). 6. Mute all other notifications on your laptop and mobile phone. This allows you to be completely immersed in the call!
5 Crucial Zoom Settings For Remote Interviews [Updated For 2020]
This is the great thing about Zoom: (Other than its reliability - although not full proof, it's more reliable than most). It offers a large amount of functionality for free. Making it a great option for small businesses or companies that are not ready to commit to a full payment just yet. This allows users to test the service and get workflows together before any money has left the bank. We have outlined the 5 important settings you need to configure to get the most out of your Zoom interview. PLUS. We have outlined our tips for a successful remote interview at the end of this article. Let's get into it. All the features you get with a FREE Zoom account: Up to 100 participants Unlimited 1 to 1 meetings 40 mins allowance on group meetings Unlimited number of meetings Online support Meetings longer than 40 minutes will need a paid subscription Prices can be found here https://zoom.us/pricing As you can imagine, Zoom have made it very user friendly so users of all skill levels can pick it up and go. They've made a load of video tutorials as well. This is how you schedule a meeting with Zoom: Easy, right? Zoom is the perfect tool to interview candidates when in-person interviews are not possible. All you need from the candidate are their email address and the scheduled date/time for the interview. That's it! You're ready to go. But. If you want to get the best out of Zoom. There are 5 settings you need to configure to tailor the service for video interviews: 1. Put the candidate name in the meeting Topic box. Makes sense, right? The meeting Topic is a great place to put the candidate's name and date/time If you’re scheduling multiple interviews, this will make it very easy to tell them apart so you can launch the correct interview at the correct time. The next tip doesn't actually make sense at first: 2. Choose OFF for host & participant video. “But I want to see the interviewee!” I hear you say. There's a reason for this Of course, you want to see the interviewee (otherwise you could just call them). BUT. It’s polite to start the meeting with the video off so the interviewer and interviewee can CHOOSE when to make the video visible to the other. This also gives them time to get that perfect angle from a usually unflattering webcam. The next setting is often overlooked. 3. Keep the audio options set to “both”. You might not intend to use the phone audio. But it’s helpful to keep the option for either party to dial in should they experience glitches with their laptop audio. It's always good to plan for every possible situation! The country dial-in options depend on where you are located. This next option will make your interviewees much more comfortable. 4. Check “Enable join before host”. What's the first rule of interviews? Don't. Be. Late. This option allows the candidate to log in to the meeting whenever they want to. If I was interviewing, I would definitely log in earlier to make sure I was familiar with the settings and controls. Especially if I haven’t used the service before (or for a while). This allows the interviewee to check their audio and video settings ahead of time. A simple but easy way to make the candidate as comfortable as possible. The next setting has caught people out in the past. 5. Make sure to generate a unique meeting ID for each interview. This can often be overlooked. Generating a unique meeting ID means that the interview is locked off to anybody else. If you don’t, it’s possible for one candidate to enter the meeting room of another, possibly whilst the interview is going on. The last thing you need is to throw off your candidate. So, that's it! It really is THAT simple to set up a remote interview. Sometimes a simple video interview won't be enough. Especially if you want to review code. This is where screen sharing becomes so useful. Learn how to screen share to present code or example work here. But first. Read our best practices for conducting a successful remote interview: Additional tips for conducting a successful remote interview 1. Pick a solid platform. None of completely full proof but tools such a Zoom and Skype will be the most reliable. 2. Video calls only! It's very easy to be distracted on a regular 'audio' call. Video meetings require singular and focussed attention. 3. Test the connection before the call. It might be best, where possible, to use a hard line rather than wifi. 4. Plan your space. As well as testing the connection, ensure that you've checked your 'interview space' before the call. Check the camera angles and distance, ensure your space is tidy and make sure you don't have any light casting shadows over your face. 5. Use headphones with an external microphone. This will capture the best quality audio (microphones on laptops are never good). 6. Mute all other notifications on your laptop and mobile phone. This allows you to be completely immersed in the call!
C++: The key to your future
Some of the hardest decisions you will ever need to make come early in your career, such as what profession to learn and where to live. Young people regularly ask me these questions, so I’m looking to provide guidance and some topics of thought when considering a career in tech. What programming language should I learn? The programming language that you elect to learn is one of the most important decisions you'll make when starting out in technology. This is because it will determine what industry you might end up in, what types of projects you support and who will hire you! The number of possible languages to programme has exploded over the last 20 years, and they all have their positives: Java is designed to work with any operating system; Python is the most accessible. But today, we’re making the case for C++, which is one of the oldest and most successful languages globally. 30 years ago, when it was first invented, C++ was far and away the most popular programming language. However, by the early 2000s, it had become slow to update and was overtaken by other, newer languages. NOW C++ is back and it’s up to third place in the charts. But why? Why C++? Let’s be honest: C++ isn't the easiest of all the languages to learn. It's very code-intensive, so you've got to be interested in writing it, but unlike some of the more lightweight languages, it is extremely scalable. It will work as well running a complex embedded machine as it will running a small indie app, and it's still one of the fastest running languages out there even at such a large scale. Mastering C++ as opposed to an easier language is a sign that you're not afraid of a challenge, and that your work will be useful for just about anything they want to apply it to - whether that's web development, embedded engineering, apps or video games. This is reflected in the annual salaries and contractor daily rates for C++ developers in Switzerland, which can be as high as CHF 140,000 per annum / CHF 900 per day across Switzerland. C++ has also stood the test of time, having been around since the 1980s in older forms, and has a large online community of developers. You can be confident C++ will keep being updated and won't die off. Working in Switzerland Even with your attractive new skills, that still leaves a place to use them. We help people find tech jobs in Switzerland because we think it's the best place in Europe to work in the technology industry. With excellent access to some of the world's largest manufacturing, medical devices, banks and financial companies, there is constant need for technology workers. This is reflected in some of the highest base salaries and contractor rates in Europe, along with some of the lowest taxes. Switzerland places no restrictions on European citizens working in tech, and you will find a huge melting pot of fellow foreign workers to mix with because 1/3 of Zurich's citizens have foreign passports. All in all, C++ and Switzerland are a winning combination for a great career in tech!
AI in Mobility - The Drivery Berlin
In October 2019 we hosted our first AI in Mobility event in partnership with The Drivery in Berlin. This was the first in a series of partnership meetups focussing on this exciting topic. For this event, we welcomed speakers from CIrc annd Carmeq: Presentation One: IQ Sayed, CTO and John Enevoldsen, Data Team Lead @ Circ: How technology and data are shaping the future of micro-mobility. Seemingly overnight Berlin has been taken over by little two-wheelers each coupled with a companion app. Join the experts from Circ (circ.com) , micro-mobility champion in Europe for an up-close personal talk about their current ride launching Circ across Europe and Germany. What was their approach? What were the challenges and lessons learned? What are the predictions for micro-mobility in Berlin? Join us for an evening filled with insights into tech and data insights as well as challenges in the mobility environment and learn how Circ use technology to solve the urban mobility challenge. Presentation Two: Jan Zawadzki, Project Lead, Data & AI @ Carmeq GmbH How Machine Learning is turning the Automotive Industry upside down The automotive industry has mobilized the global economy for decades. German automobile manufacturers (OEMs) alone employ more than 1 million people worldwide and generate sales of more than USD 500 billion. Since a Google + Stanford team won the Darpa Self-Driving Vehicles Challenge 2006 with the help of machine learning, the industry has been undergoing rapid change. Machine learning opens up brand-new business models, from autonomous driving to smart production to personal assistance in the car. However, the use of machine learning requires a different infrastructure than that found in traditional OEMs. Technology-first companies like Waymo or Tesla threaten to overtake established OEMs with billion-dollar market capitalization. Autonomous vehicles produce terabytes of data every day. This data can be immensely valuable in developing machine learning-driven functions. However, substantial challenges remain in the way of using this data. Visit this talk to hear about these challenges to help turn the automotive industry from a mechanical engineering to a software industry. The next event in the series will be taking place in February, so watch this space!
How To Write Your Developer Resume/CV (Example Resume Included)
Make yourself stand out to future employers
Adequately covering your skills and expertise
When preparing for an interview there are really only 3 areas you have to prepare for and you can link most interview questions back to these three. Preparing for these areas also means you can answer most questions more naturally, simply by referring back to them. Basically, any interviewer wants to establish 3 key things: 1.Have you got the skills, expertise and experience to perform the job? 2.Are you enthusiastic and interested in the job and the company? 3.Will you fit into the team, culture and company? This video covers how to prepare for "Skills & Expertise"
When Will Artificial Intelligence (AI) Replace Web Development & Frontend Developers?
Artificial intelligence (AI) has made a huge impact in web development, frontend developer jobs and artificial intelligence jobs. This is not a case of artificial intelligence vs web development; they have to work together. Artificial intelligence in web development/web design is becoming more and more common and the impact of artificial intelligence on web development is clear. We can see the rise in artificial intelligence popularity grow rapidly here: We held a webinar about this exact topic with Francisco Ramos, Expert Frontend UI Developer at Move Digital AG, and Charles Ahmadzadeh, Co-founder of Bunch.ai. They both gave us their views on if artificial intelligence can design websites and how it is going to fit in frontend and web development (you can watch that webinar here or watch directly below). By the end of this article, you'll know the benefits of artificial intelligence (AI) in frontend development, where it's already being implemented and what the future holds for the technology. Keeping ahead of the curve in the technology industry allows you to better serve your customers, clients or employer. Lucky for you, that's exactly what I'm going to share with you in this article: When will artificial intelligence (AI) replace web development & frontend developers? Let's get into it: Artificial intelligence (AI) is already assisting with the design of websites. Before we get too far into this, I think it's important to say: The most important thing to consider for a website is how easy can the user find the information they're looking for. It's as simple as that. Websites have become more and more complicated as times goes on, but the most important factor is still the user experience. Artificial intelligence (AI) should be used to enhance the user experience or reduce the frontend developers workload, not complicated things. Frontend development is advancing at a quick rate and artificial intelligence (AI) is helping fuel this, especially with making developers more productive. For example: Have you heard of Sketch2Code? This tool from Microsoft claims to "Transform any hands-drawn design into a HTML code with AI." Pretty cool, right? Sketch2Code detects design patterns, understands written text, understands the structure then builds HTML. You can see something very similar in action here: The difference in the GIF above is that this is happening LIVE! I'm sure I don't need to tell you how this could potentially save a lot of time for developers. It could also open up the door for more design-focused people to get involved with web development early on in the process. Does Sketch2Code and other similar tools mean that artists and design-focused individuals are going to start building/designing websites more and more? User experience needs to be considered of course, and there are certain aspects of websites that users have come to expect, but it's still interesting to think about. Artists and designers will certainly have a different idea on how a website should look, which might be perfect for fashion or design brands who are trying to stand out against the competition. Looking at languages and programs that are falling out of favour is an interesting way to see where the technology industry is heading. We decided to take a deep dive into PHP and explore the future of it. You can read that article here or watch the full webinar here. But, back to artificial intelligence, did you know: Artificial intelligence (AI) can help detect bugs too. A group from Microsoft Research, along with Cambridge University, set out to create a model that would detect bugs that no compiler or inter-unit test would be able to find. The DeepCoder is a data generation strategy which models the input-output sets and algorithms for searching over program space - the model is able to write code and learn from a small description of the problem. Here's how it works: You feed the machine a small description of the problem and it will write a few lines of code and try to solve said problem. Though there are some big limitations with this process: the machine can only write in lines of code. Also, there are other experiments that all come with huge limitations, which are not reliable enough to write production work. Pretty interesting stuff, and the model will only continue to improve with huge corporations like Microsoft and Cambridge University working on it. Did you know artificial intelligence plays a major part in healthcare too? Teamed up with blockchain it can be a formidable force. We take a look at this topic in more depth here. Artificial intelligence isn't only limited to web development though: Artificial intelligence is an important part of user experience as well. Let's not forget that artificial intelligence can also be used to enhance the user experience. I'm sure you've all seen one of these pop up at some point in the past week? Chatbots have been integrated into websites for a while now to simplify peoples experience on websites. They can direct people to different areas of the website, answer FAQ's and connect you to the employee who can best help you. A great example of this is Roof AI: The user has received a quick and easy service, and the employee has been sent a lead directly with information attached. What more could you want? Artificial intelligence aiding user experience has a lot of room for growth as well, which we'll talk a little bit more about later on. But on the other hand: AI cannot replace frontend developers in specific tasks. The main question here is whether artificial intelligence could replace frontend developers, which is really asking whether AI could write code. There are a few examples which help put this idea into context: Andrej Karpathy, the director of artificial intelligence and Autopilot Vision at Tesla trained a multi-layer Recurrent Neural Network (RNN). Andrej used an entire Linux repo on Github and compacted the data onto a single, giant file – 500MB of C code to be specific. He then ran a few key functions. With everything in place, including the variable parameter, conditional loop, property indentation, the model functioned adequately. Although he found some mistakes and it didn’t do anything useful, the code did look quite good Pretty good start. Francisco Ramos elaborates on the limitations of the model above created by Andrej Karpathy: "Software developing requires a good understanding of the problem and the business; essentially it requires intuition. We know machines are very good at finding patterns and humans have no chance when competing against machines in infrequent, high-volume tasks but when it comes to solving a problem it hasn’t seen before; machines don’t perform well." Francisco doesn’t think that machines will be able to develop intuition and the ability to interpret business values or features. "I'm certain that machines will evolve to write code one day, although I do not know how reliable this will be." says Francisco. It’s important to not forget that machines will take our code as a reference and will help us along with our workflow. Which means developers will always be needed for that initial input. This further strengthens the idea that AI is able to enhance frontend development, rather than replace it. So, the question remains: What does this mean for frontend developers? It wouldn’t be a bad idea to actually learn about artificial intelligence and machine learning. Francisco says that he has used the framework Tensorflow.js in a few personal projects already. "Tensorflow.js can be used to import models and build and train outside browsers; but it’s also used in building and training, right in the browser using the user GPU." says Francisco. Why would you need machine learning models in the browser instead of in the server-side? "It is GDPR friendly as data never needs the browser; there is no need to send any data to the server (providing better user experience)." says Francisco. Imagine the browser has access to all kinds of sensors today on user input, this would be a great source of user input to play with. You could basically interact with a website by just gesturing, thanks to the library. With Tensorflow.js projects, you don’t need to install a heavy libraries framework, compiler, and interpreters. It’s all in the browser. Here's the deal: Frontend developers should keep an eye out on how the latest technologies are evolving; it is part of the job to be up to date with the evolving technologies - you’ll be replaced quickly if you don’t. The pace it can happen at can sometimes be scary. But you're probably wondering: What is the future of artificial intelligence, frontend and web development? Charles told us "In a couple of years, websites will become even more adaptable and will be able to understand the personalities and emotions of their users when they interact." The website will eventually be able to adapt to these emotions to deliver either a better experience, but also from a business perspective, this will allow for an optimised conversion rate through different funnels. This is crazy. It's also worth noting that a lot of people believe artificial intelligence is going to actually create more jobs instead of replacing humans: In the end, if a company is using certain technology, there should be a reasoning behind it; it shouldn’t just be because artificial intelligence is impressive. This is one of the paths where technology will go, in providing a clear route on investment for a company that would deploy this in their frontend. However, there is a problem that is very frequent and has been yet to be solved. This is the problem of software estimates in predicting bugs and risks. Machine learning could actually be very useful for this problem, in not necessarily replacing predictions but by providing additional data points so that software engineers could make more informed decisions to estimate a user story. If we were able to, we could map out how much code would be needed to be built for a user story and how we’d understand this in the context of the company or the team building the product. Again, this is about tailoring and customising the experience to the user who is using the algorithm in this context. This could actually help developers better estimate, and going beyond estimates, helping with their ability to predict the impact on the maintainability of the codes. I’ve seen a lot of responses saying that artificial intelligence will never replace frontend development. However, there are lots of ideas on where it could go in the future to help frontend developers. Personally, I don’t see a future where developers won’t have a job, but I do see a future where AI will allow them to create better user experiences. In the future, AI will allow developers to have more time to explore other parts in their development process. A company hiring for an artificial intelligence position usually face 4 BIG problems, which I talk more about in this article. Often time is wasted, they're looking in the wrong places or there are issues with ethics. WATCH THE FULL WEBINAR HERE:
We were shortlisted for the “Best Client Service” at the Recruiter Awards. Here’s why.
I think you'll agree, ensuring that you keep your clients happy, and adapting your servicing offering to be able to continue to do so, is a huge part of what makes a business work. Focusing on client satisfaction is important to us, but what we truly care about is our client experience - a client being “satisfied” isn’t what we’re aiming for (we want much more than that). Finding out how a client feels about their experience with us gives us a much richer image of what we’re doing well, and what areas we should spend some more time on. Having our consultants work so closely with clients means that this feedback can be communicated to all areas of our business, in near real-time – making us agile and flexible in our services and approach. Recruitment is what we’re really good at, but we offer so much more for our clients and this is why we were shortlisted for the Recruiter Awards. Our client service offering can be segmented into 3 clear strategies: Building and nurturing communities of skilled talent across Europe and the USA, giving tech professionals the opportunity to learn from their peers. Working closely with our clients to analyse their employer brand, benchmarking them against their competitors and offering a platform, via events in the aforementioned communities, to showcase their innovation and culture. Offering detailed market updates, salary benchmarks and other up-to-date recruitment insights. Our events strategy creates large communities of technical professionals and provides a platform for attendees to network and learn from other businesses or industries This strategy also gives our clients the opportunity to show these technical professionals what they can offer as an employer. Often, these events will be held in the client’s offices which is a great way for attendees to learn about upcoming projects and ongoing innovation and speak to current employees to get a general feel for the company. We held 21 physical events across the globe in 2018, and we’re really proud of that (you can see all of our events here). We connect the right people at the right time. Part of our success is putting all the right people in the same room at the same time and our greatest success with events like these has been working with a blockchain investment company. An investor attended one of our events and reached out to us as he was planning on investing in this blockchain investment company. He wanted to work with a partner who was embedded within the local tech community to not only source talent but to grow the company’s employer brand. He understood that with so many tech companies hiring, a strong employer brand can help make the right companies stand out. We helped that business hire 13 key players within a 9 month period. And that's not all: We use data for our decisions. Our ability to spot trends in the technology market is also extremely valuable to our clients. We work with businesses and job-seekers globally, and have hundreds of weekly hiring requests, resulting in huge amounts of data for our Business Intelligence Analyst to use. This means we are able to predict how long it will take to fill a position, what the average salary will be, where the candidates will be located, whether they are predominantly active or passive and whether those hired were native speaking. We also reinforce and support these numbers with knowledge and insights from the consultants that work those markets daily. This data is all assembled in our monthly regional market update and released to our clients for free download. We release these Market Updates for all the major locations we recruit in Berlin, Hamburg, Munich, the Netherlands, Denmark, Norway, Sweden, Switzerland, Boston and New York (you can find them all here). This means the information we send to our clients is always regionally specific, and never more than a few months old. Information like this allows our consultants to speak with companies and make well-informed data-driven decisions. Knowing which technologies are stabilising, and which ones are likely to become more popular can help with future-proofing the company and their hiring plans. But, it's important to remember: Not everyone is the right fit. Over the last 12 months, we worked closely with an education company and hired within the following technologies: Frontend, Mobile Development, Digital Design, BA/BI and Software Engineering. Their interview process includes personality testing to understand the candidate’s key motivations. The education company aims to hire driven individuals with an extracurricular passion for technology, so our consultants had to dig a lot deeper to find the right profiles. For every 2 CVs we sent, they booked 1 interview. This means our clients are saving time and only reviewing candidates who are a good fit for their business. As expected, most of our clients have projects that are time-sensitive. One of our clients who are an investment firm were increasing the monthly volume of hires for their ventures with corporate partners. They wanted to work with us exclusively as they could trust us to deliver quality candidates on-time and within their budget. In our last quarterly review with the business, we were praised on our ability to deliver quickly and with quality. Within three months, all six freelance requirements put to us were filled quickly, with a contractor at their desk within the same month. Off the back of this, the company were confident that we were identifying the quality candidates and trusted our consultants to work directly with their managers. Without these 6 hires, there would have been drastic delays to their projects. This initial request has now evolved into a partnership, and our consultants have been welcomed to work on-site with them, for venture introductions and contractor care. I hope this article helped explain why our clients love working with us, and why we have been acknowledged by the Recruiter Awards. We can't wait for the event and finally, good luck to everyone who has been shortlisted!
4 tips when starting your career in data science (leaving academia behind)
Taking the step from academia into a career in data science can feel more like an almighty leap. However, putting in the research and planning before doing so can ensure it's a smooth transition and ensure you stay one step ahead of the competition. Want to know how... Read on... Just because your guided learning may have stopped after completing your Masters or PhD, it doesn't mean you need to stop brushing up on your skills. First off, it's time to get acquainted with Kaggle - this is your home for data science. It allows you to enter contests and compete with your peers to crowdsource the most accurate machine learning solutions and is also a great place to take additional tutorials and has forums in which you can talk with other like-minded individuals. For example, you can upload your code to the cloud and receive feedback from the community directly regarding your work. This can be really useful in progressing. Arguably a critical skill to have is the ability to analyse data using a programming language, one of the most popular being Python. It is one of the best data science tools and knowing about machine learning, deep learning and pandas will set you apart from other applicants by a mile. So what can you do... There are courses that you can take to learn more, including one in Applied Data Science with Python Specialization at the University of Michigan. Exploring Coursera will help you to find the right course for you and will ensure you are able to develop your skills in a way that will be most beneficial to your career. And there's more: On the programming front, another option is 'R' - an open-source programming language. It is used for statistical computing and graphics and is widely used amongst statisticians and data miners. It helps in the development of statistical software and data analysis. Knowing how to programme in R and use R for effective data capture will propel you into a career in data science. This is just the start: At the early stages in your career you'll need to hone your skills in statistics, industry-specific tools such as Spark and Hadoop, as well as cultivate an ability to communicate your ideas; both verbally and with data visualisation tools. I speak with budding data scientists every day and love to take the opportunity to advise on where to direct their self-learning, or even give them an idea of some of the opportunities available for people at a junior level. Get in touch with me today, I'd love to tell you more.
Should you reconsider that counter offer? (Knowing the right time to leave)
If you are considering leaving your current position, you may have already tendered your resignation. Many companies understand that there is no convenient time to replace any employee and will often encourage them to stay with a counter offer. While this may be flattering and could allow you to explore the possibility of staying at a place of work with familiar colleagues, accepting a counteroffer is only beneficial in very few circumstances. An increase in pay is unlikely to correct the underlying issues which prompted you to seek employment elsewhere. In fact, research has shown that in fifty to eighty percent of cases where a counteroffer was accepted, the employee left within a six-month period. Here we discuss why you should definitely reconsider before accepting a counteroffer...
6 best tips to prepare for your interview!
For many people, no matter the breadth of expertise and experience, an interview is one of the most nerve-wracking experiences. Many feel the strain to make a good first impression. Adequately preparing for your interview could mean the difference between landing your dream job and going back to the drawing board, so it’s important to invest some time in preparing well ahead of time. The video below will demonstrate 6 ways you can prepare for your job interview
Is PHP A Dying Language in 2020? The Future of PHP
Splunk: the data security solution taking the world by storm
For many companies, finding a data security solution that takes a wide-ranging view of your defences, weaknesses and threats is a real struggle. So by making the most of machine learning and AI tools and presenting the results in an accessible, real-time way, it's no surprise that California-based company Splunk is dominating the intersection between data and cyber security. Here's why those proficient in Splunk are in such high demand. A wide-ranging perspective One of the main benefits of Splunk is that it takes a holistic and all-encompassing view of risk, and it can see across an organisation's risk field with ease. Each node in the system – whether that's a device, a person or some other entry point - is given a numerical risk value: by marshaling leading artificial intelligence and machine learning capabilities to find which threats are the most salient and which can be dealt with later, time efficiency savings are on the cards. As an organisation, hiring a Splunk professional can be cheaper than using a complex data security system that doesn't have Splunk's prioritisation functions. So for those who are proficient in using the appliance, demand for services is booming. Splunk's competitive advantages Some cynics might argue that data security is increasingly becoming a priority for pretty much every data and cyber security management tool – but there are some defined ways in which Splunk has built up competitive advantages. First off, Splunk is capable of processing enormous amounts of data. As early as 2015, it was able to promise it could handle more than 400 terabytes of data per user per day, although it's now possible to scale up to unlimited amounts of data every day on some price plans. And it's also got an interface which to some degree hides the complexity behind the mask. While it is, in fact, a tool that makes the most of machine learning and artificial intelligence, it mimics a software-as-a-service platform in how it operates – leading to increased user confidence. According to PAC Online, in recent years up to two-fifths of Splunk's customer base has been devoted to clients looking for "Security, Compliance and Fraud" solutions. And it's no surprise. With benefits like these on offer, professionals who can install and embed this powerful data analysis tool are being quickly snapped up by security-hungry organisations. Sources: https://www.splunk.com/ (image) https://www.pac-online.com/rise-machines-makes-splunk-terminator-cyber-threats https://www.splunk.com/en_us/software/pricing.html#
Nailing your step into data science (and why Kaggle alone won't cut it)
The data science community is in a weird place right now. I work the market every day and see the same situation across the whole of the USA. On one hand, there are hundreds of fresh graduates and aspiring candidates who ooze potential struggling to get anywhere with the very few entry-level positions available. Meanwhile on the other, hiring managers are desperate for experienced data scientists and we are seeing one of the biggest talent gaps Darwin has ever had the privilege of bridging. Whilst I spend most of my time connecting experienced DS professionals with the top companies that need them, my heart goes out to all the great candidates working day-in and day-out to secure their first data science role. I wanted to share some advice on how to nail that first step, both from my perspective as well as from those in my network who have pulled it off. Here we go: Start with Kaggle A platform for analytics competitions and predictive modelling, Kaggle allows existing and aspiring data scientists to demonstrate and hone their skills by solving tough problems across many industries. Solutions must be highly accurate and to win competitions, entrants have to have a deep understanding of which solution to apply where (i.e. which algorithm is best for the task at hand). However, some have argued that for data scientists looking to enter the industry, Kaggle competitions aren’t the be-all and end-all. Why? Because a lot of the hard work has already been completed. You'll rarely find a real-world data science project that tells you what the exact question is, as well as giving you the precise data you need, already collected and cleaned. This is exactly what Kaggle does, and so focussing entirely on the platform to give you an edge over your competitors might cause you to miss some major elements of the data science project life-cycle. So what's next after Kaggle? Actually do data science Instead of relying exclusively on platforms like Kaggle, to become a data scientist you need to do data science. Identify a question in your own life or work that you believe you can answer with existing data (or data you can find) and create a strategy that enables you to answer it. This is a lot harder than it sounds at first, but once you get to the point of solving the problem, you’ll have a broader understanding of the preparation required throughout a DS project, both in terms of identifying the right questions to ask, as well as going about collecting and cleaning the data. Sounds like a good place to start, right? A data scientist looking to stand out from the competition also needs a strong business acumen and an understanding of how their work will be able to impact the bottom line. It will do you no good having an impeccable technical understanding if you’re unable to tell your interviewer how you plan to implement that understanding to make a business change. The second most common keywords for Data Science job postings is business: It's very important to companies that you understand the business side as well. Most aspiring data scientists I know spend their evenings with online courses and reading books, and while this is vital; maybe add a book about marketing or business strategy to your list, or do a MOOC on operations or finance, anything to round out your understanding. You’ll thank me later. The next one is the easy part. Demonstrate your passion Nailing your step into data science requires you to trust your ability to implement, and not just your knowledge and understanding. Remember, after you’ve entered a few competitions on Kaggle, solve a problem of your own and demonstrate the full life cycle of a project. If it’s a project that could have business implications, even better. Once you have solved the problem you identified, add it to your portfolio; but don’t stop there, tell someone about your project, your mum, your dog, even yourself in the mirror. Get used to explaining succinctly how you identified and answered a question with data, and by the time you come to tell an interviewer about it, the job will already be in the bag.
AI & Blockchain in Healthcare: Generating results or rose-tinted idealism?
Imagine a world where healthcare is dominated by artificial intelligence, blockchain, and data analytics. We're not as far of as you think. Technology is changing every part of our lives (and it's not all negative). From the way we source the food we eat to the way we get around town, there are very few areas in which technological innovation isn't making waves. The healthcare industry is no exception: artificial intelligence and other data science tools are having a revolutionary effect on the sector, causing an impact on finding people equipped to drive this change. This article will explore exactly how three different types of technology are changing the pharmaceutical industry, and what the coming months might hold. Let's get into it. AI: a silver bullet for cost-effectiveness? Let's face it: Barely a day goes by without the rising cost of healthcare being discussed in one national forum or another. In British contexts, it's often related to the expenditure of the National Health Service (NHS). In other contexts around the world, the focus is largely on the costs of health insurance – whether covered by individuals or the government. And it's a talking point which only becomes more relevant as the years go on. But there may be a solution in some cases: Artificial Intelligence (AI). As a revolutionary tool which can deliver real efficiencies, artificial intelligence can be a unifying force which delivers cost savings for any type of provider. Given that pharmaceutical costs are one of the highest outgoings on a healthcare provider's to-do list, any pronouncement which offers a way to cut these costs is often well-received by healthcare professionals. For example: Sir John Bel, the UK government’s life sciences tsar, recently disclosed that a hospital in Oxford is now using artificially intelligent tools for diagnosis purposes – which has the potential to shave over £2 billion from the NHS' budget. Yes, BILLION. The real innovation, however, lies in the private sector – and in the talented individuals who drive forward change there. All sorts of firms are now entering this market, and are innovating their way to cheaper pharma through AI. One firm named Optellum have developed an artificial intelligence tool with the potential to provide life-saving earlier diagnoses to cancer sufferers every single year: not only does this kind of development deliver direct benefits to patient outcomes, but it also plays a role in keeping healthcare financially sustainable. I think you'll agree, there's a lot of benefits to these innovations. And what about the skilled individuals behind these developments? As artificial intelligence beds in and more and more, healthcare providers begin to realise the immense benefits of mixing in some data science with their diagnostic and medication-dispensing functions, demand for these skills will continue to rise. Alongside direct social benefits in the form of improved patient outcomes, it's a rewarding industry path for a data scientist to take too. If you're looking for a new job as a data scientist, you can view our live roles here. And we're not done there: Blockchain is the next step In the minds of most people, the word "blockchain" evokes images of cryptocurrencies such as Bitcoin. In reality, any blockchain professional worth their salt will know that the situation is much more complex – and that blockchain has a lot of diverse applications (including in pharmaceuticals). Here's one example: The sector-specific problems that blockchain can at least increase the chances of fixing are diverse, but perhaps the most pressing one is the risk of fake drugs. In the age of the Internet, this is a real problem. The dark web enables people to self-medicate by buying drugs from unspecified sources. Consumers who think they are going through legitimate channels may discover that they are being scammed with fake – or even dangerous – spoof drugs. According to the World Health Organisation (WHO), for example, 10% of every single drug which circulates all but the high-wealth countries are either fake or what's known as "low-grade". This is crazy: Attempts to regulate drug manufacturers and maintain databases using traditional technologies are out there, but they're vulnerable to all sorts of problems like hacking. It is thought that blockchain could offer some defense against this problem. As a decentralised and highly secure technology which isn't administered by a central authority, it's next to impossible to hack a blockchain-powered system. If all patients, medical practitioners, and pharma companies could participate in such a system, it could well have more legitimacy than any pharma database system in history. So while blockchain professionals are often in high demand due to the needs of finance companies, it's likely that in 2019 a broader understanding of blockchain's many use cases will emerge – and pharma will be high on the agenda. For a skilled blockchain professional, this will represent a spike in demand and no doubt huge salary growth. As if that's not enough: The genius of new medications Understandably, challenges in pharma – and how they intersect with tech – are often dealt with in terms of commercial or security-related focuses. However, for those tech professionals who are interested in working at the cutting-edge of medical technology (and in making a real and direct difference to patient outcomes), 2018 held lots of developments and innovations – and 2019 is likely to hold even more. Just this month, for example, it was reported that gene therapy firm Novartis' CEO sees his firm's muscular atrophy gene tech Zolgensma as "potentially foundational medicine". Novartis was the first-ever pharma firm to secure worldwide permissions for gene therapy – and with many other firms out there leading in such an innovative way, you're sure to have an exciting experience if you decide to apply your tech skills to a firm which is changing history. Overall, what's clear is that when it comes to pharma, the competitive edge that mastering technology gives is not going away. Whether it's cutting-edge new medical tech, the impact of security tools like blockchain, or even the efficiency potential of artificial intelligence, there's a whole host of choices for tech professionals looking to make their mark and develop a rewarding career.
Tackling competency based interview questions - Answers, what is your biggest weakness?
Darwin have been Digital and Data recruitment specialists since 2001, and time and time again we have seen candidates fall down when answering one question in particular; "What is your biggest weakness." Here we give an insight into the pitfalls of answering this question and advice on the best way to answer it.
How can tech start-ups showcase an employer brand to compete with FANGs in the war for talent?
Hiring tech staff in New York can be difficult for any employer. But it's even more demanding for tech start-ups who are competing with FANGs to secure the best talent. FANGs being an acronym for Facebook, Amazon, Netflix and Google, the four technology giants trading publicly in the market today. Attracting the skilled individuals needed to drive any tech start-up forward is essential for the ongoing growth and profitability of the business. However, with the niche skills required in such high demand and with competition so fierce, it’s an uphill struggle. Let's get into it: Growth of New York's tech start-up scene The New York start-up scene is thriving. Venture capitalists pumped $3bn into the start-up scene in 2017 alone, and many of these fledgeling businesses are tech start-ups themselves. So far this year, venture capitalists have more than tripled this figure and invested $11bn into businesses. Some of the top 2018 start-ups include online wedding planner Zola, technology real estate platform Compass, lifecycle management platform Braze, and cloud-based medical imaging supplier Butterfly Network. Rather than piling funds into Silicon Valley start-ups, investors are seeking out promising, homegrown businesses with the technological capabilities to grow New York’s infrastructure; provide ongoing job opportunities and income generation. You might be wondering... What does this mean for New York tech start-ups hiring talent? The continuous growth in New York tech start-ups means it's important to attract and retain the brightest and best talent. This can be extremely difficult when you're up against tech giants like Google, Facebook and Amazon. Although this may be disheartening to tech businesses, there are ways for start-ups to attract top talent without the necessity of competing on a level playing field. Despite all the incentives and perks offered by the tech giants, they still only hold on to employees for around two years on average. Why do we think this is? What should tech start-ups be offering to leverage the high staff turnover from these businesses? We’ve spoken to our candidate base in New York to gain more insight on this topic. On one hand, many agreed that working for a huge brand is extremely attractive for tech professionals; their name on a CV alone will set the candidate in good stead for their future career. On the other hand, tech professionals often miss exposure to those at the forefront of a business and thus the opportunity to offer valuable input to the future and vision of the company they work for. One of the most attractive features of tech start-ups is fantastic leadership and the opportunity to work in a new, exciting business that's setting the ground rules. A great founder can build an impressive tech team with an inspirational company culture which filters from the top down. Of course, maintaining impetus and business growth is vital for tech start-ups, but it's also important to create a company culture and unique employer brand from the outset. Creating a strong mission and identifying the core values of your tech start-up are essential for creating a strong business culture needed to attract the very best talent. Skilled tech professionals feel very passionately about technology; it’s these people who possess a knowledge of technology and how it can be used to drive a business forward. That knowledge and understanding is often overlooked in a huge business where every employee is struggling to be heard. Whilst many job seekers are enthusiastic about the flat hierarchy, exciting projects and instant gratification that’s associated with start-ups, there is a perceived risk that goes alongside joining a fledgeling business. Strong communication and education surrounding the funding, goals and vision of your business as well as a clearly defined culture are definitely the ways to highlight the strengths of your start-up, enabling you to provide confidence to job-seekers in overcoming any pre-misconceptions. This strategy also places your start-up in the best position for the battle against giant companies in securing the best talent. So, How can Darwin help you showcase your business? Over the last 12 months alone, Darwin has worked with over 100 business across the globe to help showcase their employer brand; providing them with the platform to promote the people driving their business forward and the technology they are using to do so. As well as endorsing the strong culture and goals of their business, which helps them to stand out amongst the tech giants. We host monthly meetups across Europe and America showcasing skills and technology from the world’s most exciting start-ups alongside global brands such as Wayfair, TripAdvisor and Microsoft. Our clients often host these meetups at their offices to showcase their culture and working environment. All our events are live-streamed to offer continuing exposure for your business. At Darwin, we are extremely active in the tech community and are passionate about sharing knowledge and expertise amongst like-minded people. This dedication and interest in the tech community allows us to personally engage with the talented individuals required to make these meetups such a success. These events often showcase technology and innovation on a larger scale, but we regularly host webinars and hangouts that offer an in-depth investigation into subjects that are highly focussed. Again, we invite our clients to offer their opinions and advice on such topics, encouraging as much engagement as possible with those involved. These events are also broadcasted live and shared within our community on an enduring basis. Interested in partnering with Darwin so you can showcase your innovation and culture? Then do not hesitate to get in contact with me and we can discuss future partnership opportunities.
4 Biggest Issues Faced by AI Businesses When Hiring
Did you realise that recommender systems have been implemented into various aspects of our everyday life? Well, one of our speakers from our recent Data World Tour, discussed what recommender systems are, and shows us where we may come across them. He also takes us through any problems that may be encountered when working with them and how’s best to overcome them. Kim Falk, is the Senior Data Scientist at LiveIntent, and spoke at our Copenhagen stop. We had a really insightful talk from our first speaker, who discussed the involvement of AI in the healthcare industry, specifically looking at how it has been used in drug discovery research. You can read the article of his talk here. Our third speaker also spoke about Machine Learning (ML) and the influence it has on customer satisfaction in banks. You can read that article here. Anyway, Kim begins his talk by clarifying what is meant by a recommender system. A recommender system is one of the most successful ML systems. It is a system that predicts a user’s interests and recommends items that are likely to be interesting for them. It gets its content by filtering through information and data that has been fed into it by the user themselves. Spotify is an example of a recommender system since it gives music recommendations based on what information you’ve fed it, through what music you’ve already listened to. Netflix is another example of a recommender system, giving movie recommendations based on what movies you’ve watched before. You teach a system what your taste is, so whenever you open it, it comes up with what you’ve searched before. Now: There are two different types of recommender systems One type of recommender system is collaborative filtering, which focuses on using the behavioural data of users or interactions between a user and the content. The other type of recommender system is content-based filtering, which uses the content, the user and the metadata that can be collected. Kim first takes us through how to do a recommendation with a content-based filtering system. For each item, you find similar items and create a list of all items found which is then sorted by relevance. If you have a user profile, which is a list of consumer information, you can extract metadata out about the content in this case, from using the information from tags, facts and content descriptions. When processing currents about the content-based filtering, you don’t need to know much about the users. As long as you have the metadata and the content, you can find similar things between. One of the biggest problems with content-based filtering is that most people want recommendations on content outside of their usual taste, but the system won’t have any information on this. For example, it may be the case that the user hasn’t watched any movies from a certain genre before but wants recommendations. Another problem with content-based filtering is similarity. When a content-based filtering system works well, good recommendations can be offered. However, you are in danger of the system offering the same thing all the time. On the other hand: Collaborative filtering is about the connection between users and the content There are two types of data in collaborative filtering. One data type is explicit, which is where the user is asked to give a rating of their content, for example, being asked to rate a movie out of 5 stars. The other kind of data is implicit, which is where you log the user’s actions on the site. As you are logging a user’s behaviour, you will need to create a rating matrix which creates an overall view of all your content. With implicit data, you must be clever. You must translate their actions into ratings, so the data can be logged into the rating matrix, which can then be used to compare against other data. So, it means that if somebody bought something off the site, you’d give this action a high rating. If somebody viewed something on the site, you’d give this action a medium rating and if somebody did almost nothing on the site, you’d give this action a low rating. There’s a lot of ML which can be done to translate the data from actions to ratings. When you have a rating matrix, it looks like an easy problem, you just have a few empty spaces to fill out. However, This is hard if you have little data. You can retrieve extra data by finding similar content based on a users’ actions. This can be done by scanning all information to see if any users with similar ratings can be found, like content-based filtering where you found similarities based on their content. User lists can be collaborative. So imagine there are 3000 other people in the system, there’s a good chance that there is someone with a similar taste to you and therefore the system can recommend you something based on the similar ratings. Having a sparse data set encourages you to extract the essence out of the matrix. The idea behind this is that for example, if you had data from a type of movie genre and you tried to draw it on a graph, the data from one movie would go one way and the data from another movie would go another way. This system also tells you how much friction certain data has. For example, say you had two different movies from different genres placed on a matrix, they would have different friction. This leads to a process called Tricks Factorisation, which is where you try to reduce the users into a smaller number of user factors and a smaller number of item factors. If you look at the vectors in a high-dimensional space, you can then try to reduce it to a smaller space where the information is extracted. So, if you have one graph that goes toward a movie from one movie genre and the other graph goes toward another movie from another movie genre, then we’ll have two sets of data when we just needed one direction for these two movies. This means that instead of a two-by-two matrix, we just had two factors in different places, allowing us to get a prediction of a rating or a prediction about how likely the person is to consume or buy the item. This is an issue that has complicated ways of solving it. As it turns out: Single vector decomposition (SVD) is the solution that most people look at if they have any kind of mathematics involved in the problem SVD factorises a matrix into 3 matrices and ensures that the user of each one is the user of the factors. You can ensure that the user of each matrix is the user of the factors. The matrix will have a diagonal factor in the middle which works by showing you how much information there is in each factor. This means you can take the middle matrix and then you can add up how much of the information you’d have, in the sense that if you added all the numbers, you’d have 100% of the information you had in the original data. You can choose to have only 80% of the data represented, When you carry out SVD, it looks at the matrix as a whole. Say it saw that 0.04% of the data was numbers and the rest was nothing, the data wouldn’t be defined unless you put something into these numbers. Otherwise, you end up trying to guess what you should put into these numbers, so you can do factorisation properly or else it doesn’t make sense. If you had your factorisation serviced and optimized, it would predict zeroes everywhere, meaning your matrix will be full of zeroes and you’d then normalise the reading of the data so zero is the mean. The process will still end with you predicting average rate all the time. But there’s a catch, Calculating factorisation is difficult It takes a long time, requires a lot of money and you have to put everything into memory. Also, rating matrixes are extremely sparse A solution to this issue would be to input data. But, this defeats the purpose of the recommender system. So, this decreases the dimension of the utility matrix by extracting its latent factors. It can map each user and each item into a latent space which helps us to better understand the relationship between the user and the items as they become directly comparable. It does get better, Simon Funk came up with a different version of SVD which is the neural network version and is known as SVD ++. He came up with this version on the basis that when you do matrix factorisation, you focus on all the zeroes and all the unknowns. He thought that if we have factorisation, we need to find some values of the user factors which we multiply, so we can get ratings more or less like we’ve seen before. Funk wanted to use a matrix which includes user factors, though he creates them so that he minimises the difference between their actual ratings and those factors. This solves the problem of focusing on zeroes and turns to only focusing on factors that we actually know, know these ratings then afterwards you can predict the rating. Though this is a positive, there are things that can go wrong. The model can be overfitted, which can happen when factors are specialised too much to the data, so an extra equation is put in to take care that it gets closer to the data so it doesn’t get too specialised. You end up having too many equations, which leads to the model being overfitted. There are different ways to solve this problem, however, Kim says that we can start by training our model one of two ways. You can either train your model using Stochastic Gradient Methods (SGD) or Alternating Least Squares (ALS). Kim argues that SGD is the best way to train your model but you can’t always guarantee that it’s always the right optimal solution you can find. He states that ALS is easily distributed and is the most used training method right now. One outcome that must come from your training, is that you need to focus on minimising the equations, so the models don’t become overfitted. By minimising the equations, you can also let your algorithm focus on data that is important. Another way to solve these issues is to look at the relevance to your recommender system’s recommendation. You must look at the relevance of the choice the system makes which entails looking at the context, for example a horror film wouldn’t be relevant for a Saturday morning, whereas a comedy would. Now: Autoencoders are an interesting construct Autoencoders are a neural network. They’re not a deep neural network as this has been tested out and doesn’t seem to have a better result, so just a simple neural network is used. Autoencoders can create a latent space but it also turns out that they can do a rating prediction. For each user, you train this out. Kim goes on to say that there is interesting work that should be done on Deep Learning networks, as they can consider what the next fix is and decide on what the next best action is. This can be particularly helpful in the banking industry. Furthermore, Kim states that in collaborative filtering we don’t need to know anything about the content or the user directly. If you can filter in some data from their behaviour, then we can recommend content based on this. Kim arguably says that without knowing anything on the behaviour of the user, the process will end with a content-based recommender system as you can find similar content as soon as you have the metadata. You might be wondering: What is the best algorithm to use to train Autoencoders? Kim suggests that we should build an algorithm, and then add more so we can create an ensemble using each of the implemented algorithms as an input. He also says that the content-based system is interesting, as Natural Language Processing (NLP) is coming up with ideas that can find similar descriptions of content. Kim says that most people will say that using implicit data in websites to create recommendations is what we should be focussing on. This is because you can record data quickly from them and the data keeps coming, so then you will create a matrix factorisation with collaborative filtering. Then you can take one or more recommender and use them as an input into linear regression, so this will produce new recommendations which can help solve any problems. Say I have different types of data and I want to show content-based filtering and collaborative filtering systems, both will show different things. But if you mix both the systems together, their signals will go in different directions, and together you can create a better recommender system. But there’s a catch: Recommender systems have problems with new users This is a constant problem that recommender systems deal with. What do we do when we don’t know anything about a user? We can’t offer personalised recommendations as we have no previous data, on either of the recommender systems. But, there are some ways to overcome this. If the user arrives at your page and shows interest in something, then a content-based filtering system can be used. You can make it look as though you are giving personalised recommendations by recommending popular items. It’s important to remember these items are popular because a lot of people like them. On one hand, it’s nice to receive customised recommendations, but in the end, we do like a lot of the same things, otherwise, this content wouldn’t be popular. On the other hand, you can argue customisation is more interesting, and we can do more from it. We can try to promote new content by putting it onto a new arrival list. A user would spend time exploring the new content and a content-based recommender system can be used from this. This is called explore exploit. It is a simple algorithm which every time somebody should see a choice, the system either puts in a recommendation or a new item. To keep the circle going, you need to add new data to everything. This is used a lot, for example, when talking about the news. Though you can find ‘your favourite’ new article, if you don’t have a constant circle of new items coming in, then you have a problem. Kim makes another point, that a ML model will learn exactly what you teach it. He points out that this is interesting especially in regard to recommender systems. Kim says that it’s important to ask if we had the context behind the recommendation when it was made. It might be the case that when watching the content, another person is with the user and made the choice, or even that a friend of the user’s is using their account to watch the content. Consequently, we can’t be sure that the data we are using in the recommender system is really true. Many people think that we should use DL to get more specialised models. However, In Kim’s experience, it is better if your model is buggy. This gives the system a chance to recommend things that aren’t entirely in accordance with the taste of the user. This helps users to see other content. See, the problem with always having content recommended is that you have a filter bubble and your taste will become more and more narrow – soon there won’t be any content left to be recommended to you! Following on from this, a recommender system is only as good as its content. If you have a very specific taste, then you will only be recommended content based on this. For example, if you like French documentaries, there’s only a select few that can be recommended to you soon and you will soon have none left to watch. Another factor Kim asks us to consider is that the recommender system assumes the taste of the user is not changing because we are optimising data so historical. People’s tastes are constantly tasting, but they also trust the recommender system to give them recommendations. If a user thinks the system is offering personalised recommendations based on popularity rather than from their taste, the trust in the system decreases because they are being recommended content for the sake of it. This will mean the user is less likely to use the system if the trust is gone. Kim ties this into another point he made, asking us whether we should aim to make most users happy or simply the ones we know well? This opens up to a wider discussion which asks if we aim to make most users happy, including new users, will older users lose trust through what they’re recommended? Or simply, will new users not be able to gain their trust in the first place, since the recommender system is focusing on users they know well? Though this offers an interesting point of debate, this will not be discussed in this article. Regardless of these answers, Kim says we should aim for at least one good item per recommendation for every user. To finish off, Kim claims that even though recommender systems can do a lot, but they can’t do magic. This indicates the scope of development that recommender systems have in the future.
Machine Learning and Customer Service
It's crazy to think about how Machine Learning (ML) is being used in a wide variety of different industries. On our recent Data World Tour, we stopped off in Copenhagen where we were host to three, very interesting speakers. I've written an overview on all of their talks for you. Our first speaker, Gopal Karemore, discussed how AI has had an impact on the healthcare industry as well as drug discovery research for many different diseases, such as breast cancer. Our second speaker, Kim Falk, gave us an overview of recommender systems and problems that they bring but offered us multiple solutions to these problems. Our third and final speaker, Phillip Jarnhus, gave us an insight as to how ML helps to provide better customer service in banks. Philip is a Senior Data Scientist at Danske Bank. He specifically looked at how ML is used by Danske Bank to improve their customer satisfaction, provide predictions, see whether these predictions are accurate, and how they need to be altered if not. Even though Philip discusses ML in relation to Danske Bank, it’s important to recognise that the insights he offers can be applied to other real-world situations and companies. He didn’t discuss a specific ML model, but rather focused on the general challenges faced when working with ML models at Danske Bank. The group Philip works for is one of 3 centres of excellence in terms of advanced analytics. They focus on credit, credit risk and money laundering. As a Data Scientist, Philip’s main work includes predictive analytics where he works to develop predictive models; these predictions can take place anywhere from 3 months to 3 years. He states that if they can’t measure an effect within a couple of months, then they’re not carrying the project out well enough. Here’s the deal: Advanced analytics can help create customer satisfaction From the analytics collected, Philip’s group can create customer values by linking the analytics to the strategy that’s in place. Part of the strategy is to make the customer happy, so they stay with the bank. This is key to growth over time. This is why customer satisfaction is so important to the bank. Philip also tells us that the group starts with as little data as possible, so that they have room to grow, move upwards and with this comes a lot of education. The group can start to build user stories which will contribute to the education. This is beneficial as the rest of the business can learn to understand the strategy and what the group is working toward. They need to see that the process is working before it starts being adopted. Finally, the group needs to execute the plan, so they can measure and communicate the impact it has on the bank’s customers. Philip explains that out of a 6-month product cycle, you’d spend at least 1 or 2 months at most doing the product modelling, while the rest of the time is spent on understanding the business and going back to measure the impact. The bank needs to make sure that it has everything mapped out, so it can clearly view what’s working and what isn’t. This also points the bank in the direction of what needs improving. No doubt about it: Relevance is key The bank uses commercial analytics to make sure it's relevant to the customer. Commercial analytics lets the bank use the current surveys asked the customers to see what’s irrelevant and what’s relevant in customer satisfaction. The bank doesn’t want to provide a customer with some sort of contact or communication that they don’t see as relevant; this is likely to leave them less satisfied than if we hadn’t contacted them at all. You see, relevance affects customer satisfaction. Advisors are a good asset to the bank and have been proven to have a positive and powerful impact on customer satisfaction. Advisors are able to deliver good customer experience and fix model shortcomings in real-time; however, they are expensive in comparison to digital channels like a chatbot. Philip points out that every time the bank contacts a customer, they’re taking a gamble. But, the group does everything it can to chase so it can be as relevant as possible to the customer. If the bank is in a purely digital world, it can have a good feedback loop in place which puts the resolved approach in motion. This means issues get resolved quickly and feedback can be given right away. All the bank’s sales go through an advisor, so essentially if they didn’t get the approach right, the advisor can fix all the shortcomings and steer in the right direction afterwards. Since they are expensive, the advisors are only needed for relevant cases. Philip explains that for other cases, the bank can afford to be hit and miss in a digital channel. Ideally, the bank would have an advisor available for every customer, however, they can both fight and benefit from having one due to costs but benefit from the customer service it provides. As it turns out, Relevance can’t be measured It can be perceived, but Philip gives us a breakdown on what it includes. There are 4 main areas we can break it down into. The first area is the channel. This looks at our choice of communication: does our choice involve a letter, person, phone call or another digital channel. There are also factors to consider in this: Is there a preferred channel by the customer? Should we respond in the same channel as the customer contacted the bank in, say they sent their message in an email, do we then call the customer? This will possibly give the bank a chance to get feedback. The second area looks at the content of the message. This also considers other factors such as tone of voice and how we should talk about our products. The third area is timing. The bank needs to consider what it is exactly what the customer is looking for and the timing of communication in regard to this. So, the bank needs to consider what it is they are showing to the customer and when they are showing them this. For example, the bank would question whether they are able to get more product sales on a Saturday morning compared to a Tuesday afternoon say when the customer is at work? The fourth area is familiarity. This looks at how well the bank identifies itself with the customer because this gives them more or less leave on how they talk to the customer, how they build a relationship and what subjects are acceptable to talk about. If the bank wants to build up a level of trust with the customer, they may use a message such as ‘welcome to the bank’. However, if the customer has been with the bank for years, they won’t want a generic welcome message, so they have to hit the right level of familiarity. Also, the bank needs to be wary that they aren’t talking about information that isn’t needed, they need to make sure that their product information is being discussed in the right order. Sadly, There are issues with the classic use of the ML model Philip looks at how we’re using the ML model and states that the way we’re using it is perhaps not the best, however it's not the worst since the model is used as a strong algorithm. The classic use of the model prioritises which customers to contact, the predictive model sorts all the relevant customers to the left. As suggested, there are issues with the classic approach. Predicted categories are often too broad. Advisors are forced to spend excessive time preparing for a call or left searching for the right product to offer the customer. The classic approach has also been criticised for having a too-short time horizon for its prediction since three months is not sufficient enough to capture the customer early in the decision process. Leads are only sorted and not filtered, advisors often cherry-pick the customers they know in advance to ensure a positive conversation. For example, Say the bank wanted to run a campaign for an investment product, using the classic approach they'd see who'd want a care investment product in 3 months. They’d then take the top 1000 people and call them, which is essentially a sorting algorithm, there’s no sort of threshold that doesn’t filter in any way. Using this classic approach, the bank ends up having so many customers compared to how many they actually call, which isn’t the best way to use all the information. Philip suggests that the bank needs to improve on this. Since there are some other issues to consider. Say the investments spoken about in the example above are home finances. The bank would tell the advisors to talk to these people, within that there’s a myriad of products. There’re different ways you entail that service and every customer in the bank has their own unique, tailored product, depending on who they are, what they’re rated for and what their needs are. So, this essentially gives the advisor a blank slate to say something with this. The key is to find advisors and not salespeople, so they are giving genuine advice. For many machinery problems, you need a long time to predict ahead. The original prediction period is way too short, if you do say home finance and a customer wants to buy a house, they usually have a year or two to think about the process. The bank aims to get customers on board as early as possible so that they can help steer the bank. This means that the customer will end up having a home finance mortgage with the bank, but also receives a good customer experience with the bank. The last issue is that all leads become available to all devices. There’s no filtering method, just a sorting method, so the model can go through what ones are most likely to get a good customer experience. So, they choose customers they already know, essentially carry out collaborative filtering, but they filter the customers based on their own experience and what they’re trying to solve. This also means that they’d had to evolve the text to include more modern content. Philip explains that Python is prevalent in many areas of the bank and they are going into Deep Learning (DL) within the next year. DL hasn’t been relevant in the bank before until now because of noise levels in other stages of the process. DL couldn’t provide enough for the bank to use and they would rather have a rapid prototype to use in seeing what customers had said, rather than spending a year or two building an architecture of a neural network. The types of problems the bank is dealing with, can’t do a lot of transfer learning, so that’s why DL has been sitting back. Philip takes us through four different examples of how they’re trying to ‘break the curse’ of the issues they had previously. Providing early warning signals for customers leaving early So, one of the issues the bank had is that identifying people leaving the bank 3 months ahead, was way too short for anyone to do anything. By that point, the bank had had their last plateau where you have that number one in the image above, which is where most of their churns came from. But, customers had already started moving their mortgages etc. even when getting back in touch with them, they have no save rate. The bank could tell they were churning in the next three months, but couldn’t do anything about it, so they needed to extend further back, in order to be able to estimate proxies. The bank needs to be 3 months ahead of the customer either moving their mortgage or unit number transactions, anything that acts as a predictor. So, the bank moves the prediction time back, giving themselves 6-9 months of heads up for someone actually leaving them, without having to extend the data. If the bank were to go more than 3 months back, they’d need a lot more data to actually make their predictions. Predicting product level rather than category level The bank moves on from a model based on internal business definition to the customer situation. They attempt to predict the product most likely to interest the customer. This leads on to the bank giving an advisor an entry point into the conversation with the customer. The advisor starts the conversation by asking if the customer has heard about the product. It might make more sense to start the conversation this way, rather than straight into finding out if the customer has enough money to manage one of the investment products. This is because that process usually takes a fair bit of capital to get into, so this way the advisor can actually get into the product level predictions and begin the work in progress. Predicting first time home buyers The predictive model catches patterns in the behaviour of previous first-time buyers in Danske Bank and uses these patterns to identify potential first-time homebuyers in the existing customer database. This aims to capture customers at earlier points in their home-buying journey. What matters to customers most is getting the product, in the case of this example, their home. When buying a home, the customer generally thinks about the process of getting a home, explores their options through other websites and decide on which bank they want to get their mortgage with. For the customer to get into the bank, they start receiving cards and pushing out a few other products, so they can start being educated on their home mortgage. It is a long process to buying a house. Breaking down the customer journey The bank think of the customer's journey as a funnel, where at each step, less and less people move forward. There’s a significant number of churners which is an issue. The solution to this is to focus on individual steps and not end-customers' problems. Advanced analytics can also be used to fix pain points. By fixing these issues, the bank can hope to drive more customers to success by increasing customer satisfaction. Most people change banks, which is a prime opportunity and a ripe market to get new customers from. Danske bank needs to make sure that they predict every step of the way where they can, so they can keep in check with every touchpoint. If a prediction looks like it's about to go off scale, then extra attention is paid to it. So the bottom line: Philip knows that Danske Bank still has room to develop and that their ML models will become deeper as the bank moves forward. Though advisors are a great asset to the customer service, it’s impossible to use them for every customer. This is where Philip sees the bank improving the most, as they continue to grow.
Machine Learning Now Understands Fashion
Did you know that machines have been taught to understand fashion? For some while, machines have been able to understand the context of a picture, but now this has gone a step further This is exactly what I’m going to be talking about in this article. We recently held a Data World Tour which took us to 7 different cities, listening to a wide range of different speakers. One of our stops took us to Berlin, where we listened to some really insightful talks by speakers who all discussed varied topics in Data Science. Our first speaker, Conor Digan is the Senior Data Scientist at Outfittery. He spoke about how Outfittery have implemented Machine Learning at the core of their business, to both speed up processes, and increase customer satisfaction. Best of both worlds, right? We also had other speakers on the night discuss how Machine Learning has been used to predict car and property prices (you can read my overview of their talk here). But first things first: A quick introduction to Outfittery At Outfittery, they’ve taught machines to understand fashion (Outfittery are an e-commerce company for men’s clothing). You order a box of clothes from them, and a personal stylist chooses the clothes, packs the box and sends straight to you. Once you’ve received the box, you keep what you want and send back what you don’t want (only paying for what you keep). I'm sure you've all seen apps and services like this advertised. But: They discovered a problem in providing product recommendations to a set of customers, which turns out to be a standard problem of any e-commerce company. E-commerce companies want to provide recommendations which are the best product for their customers, but recommendations that are most likely to result in a conversion (a purchase). From this, they can try and sell similar items to similar customers that they’ve already sold products to - this is a standard procedure for any e-commerce companies. Now, let’s get into it: Recommendations are made by both humans and AI At Outfittery, there are a couple of quirks that change depending on how they need to make a recommendation. First, any recommendations that are shown to customers are a combination of human and AI recommendations. So, any recommendations the Data Science team make (or any that their models make) gets shown to the stylist. The stylist can then choose to ignore or use these recommendations where appropriate in order to pack the box. This brings around obvious differences in any implementation or in the exact kind of optimisation goal itself. Conor claimed that there must be a potential somewhere on loop for humans to learn something from AI. The biggest problem faced by Outfittery is the cold-start problem on steroids. The cold-start problem itself stems from where you get a new item of stock that you’ve never tried to sell before or never shown to customers before. This means you have no good sales data to look at what kind of customers even like the product. At Outfittery, they face this problem on a much bigger scale, every 6 months, their entire stock changes with new items ready for the new season. Not only do they have a huge influx of items that they have no sales data for, but they also stop stocking all the items that they do have sales data for. To try and overcome this problem, instead of using the data from the item, they try and use predictor variables to predict how the items will sell. The third problem Outfittery face is that if, as a customer, you’re not going to be able to predict whether you’re going to like something by reading the description, then how can you expect an algorithm or a computer to predict whether you’ll like it. To overcome this problem, Outfittery has to use image data in some way if they are going to make proper recommendations to customers. This leads Outfittery to using a standard classification network, where they feed their data through an input vector, which is then fed through the network in order to try and predict the outcome. This process has been shown to work quite well. An advantage of this method of classification is that the network is relatively simple to build and provides great libraries by doing this quickly. However: The network provides zero insight as to why it predicted x or y. This means Outfittery can’t use it to feed much information back to their stylists. The biggest disadvantage of these networks is the huge amount of training required to build a useful network. The network has to map out the relationship between each individual pixel and whatever it is they’re trying to predict. Now, Imagine you could compress all the information stored in an image down into a much smaller vector... Autoencoders can do just this If your training data is an image of a pair of jeans, it will try to predict the exact same pair of jeans at the other end of the network. Now, on its own, this does not sound useful. What makes them useful is that in the middle there is an embedding layer which has a small dimensionality where the data is forced through a small layer. The decoder must then recreate the image from that small embedding. For example, if you’d had a code size of 10, so the embedding layer only had 10 different numbers, the decoder was actually able to recreate the 8 training images to any reasonable layer of accuracy. There must have been a large amount of data stored in these 10 images. Once you have this encoding, you can use this for any standard classification regression Machine Learning in general. There are some consequences of this. One of the consequences is that as a result of it being a much smaller network than the original, in pushing out less noise, it requires a lot less data and a lot less computational power in order to train the network. This is just the basic version of an autoencoder. Conor then takes us through some different versions. One of the simplest is the denoising autoencoder. This is essentially the same as the normal autoencoder, except the input image has random noise added to it, compared to the output which remains clean. The network is trained to predict a clean image from the one with noise added to it, so this will result in a more robust encoding. This type of autoencoder has some direct, practical uses; the most obvious being that it denoises images. If you’re in a process that gets in noisy images, all the time or part of the time, then Conor explains that we can use a formula to help denoise and then the image can be used as normal. Similarly, the autoencoder can be used to denoise non-image data, such as attributes of an item of clothing. One of the biggest problems with these types of autoencoders is that their embeddings end up occupying quite narrow pockets in the latent space. One of the most powerful uses of these auto-encoders is that they can generate new data that has been previously unseen so that it's completely outside the training data. Conor wonders what would happen in the process if we submitted half a t-shirt and half a shirt. He says that say we get to the halfway point between the vectors, and then can put it through the decoder, so the model can output pure noise. It wouldn’t look like an item of clothing, because the model has never seen something from this space or doesn’t understand what something from this space looks like. Conor explains that there are similar use cases as the one above, you can use this process to see what a half rock and half classical song sounded like if you had encoded a lot of different songs. You can also use a vector arithmetic to figure out what specific features look like. So, an example of this would be that if we had a human face, we could see what that face would look like with a pair of glasses added to it. Or, what an item of clothing would look like with a pocket added to it. You see We need to enforce some sort of regularization This leads Conor on to discussing the concept of variational autoencoders. Instead of mapping or encoding onto a single deterministic vector, you encode said maps onto a vector of gaussian distribution. So instead of having a single vector, you have two. One vector represents the mean of your distribution and the other represents the standard deviation. To go on from this, instead of feeding the model through these deterministic vector numbers, you can then sample from the distribution and then it goes through the decoder. So in training this, if you input the full image and you run it through your decoder, it will predict the new vector: a standard deviation vector. Then you can sample from this and feed through the decoder. This on its own doesn’t solve the problem, to solve it we must introduce some form of regularization into the process. Conor explains that we can enforce some regulation by introducing the loss function. The loss function is made up of the reconstruction error and the Kullback-Leibler (KL) divergence. The KL divergence measures the distance between the two distributions and in Outfittery’s case, KL’s divergence can measure the distance between our predicted distribution and the standard normal distribution. By minimising this, we try to minimise both the reconstruction error and our predicted distributions distance from the standard normal distribution. Now, The beta term is added in to tune the parameter that controls the trade-off between reconstruction accuracy and generative ability. On the left of the image above, the graph shows what would happen if you trained using only reconstruction loss. So, if the value of beta was zero, you have the same problem as earlier where you have these pockets of space where the decoder has no idea what it means or how to interpret it. In the middle of the image, is the graph that shows the model being trained with only KL divergence. This means that the network is only incentivised to try and have your predicted distribution or every predicted distribution as a standard normal. So, by combining both, the model is able to provide predictions and recommendations for items of clothing that should be used by the stylists, along with using a really simple vector arithmetic in latent space. How can you actually use this in application? Autoencoders generate samples and benefit the business for Outfittery As mentioned before, the model can be used to figure out what half rock and half classical sounds like. If you had a single rock song or an average mean vector of all the rock and classical music you input, you can just get the halfway point between their two vectors and then feed that to the decoder. This will then output whatever half rock and half classical music sounds like - the model can also generate specific attributes. If we wanted to figure out what a glasses vector would be like and we wanted to add glasses to a human face, then we’d need one image of a human face without glasses and one image of a human face with glasses. We’d then encode both of these and then the difference between their encoded vectors will be the feature of having glasses. From this, the glasses vector can then be used to add on to any other face. In a similar way, this process can be used to figure out a pocket vector to see what pockets would look like on a shirt. Autoencoders provide benefit to business for Outfittery. At Outfittery, they use autoencoders to solve actual problems. Autoencoders can predict missing attributes. At Outfittery, they have lots of items of clothing in stock, with lots of attributes for them and some of these attributes are missing, which is a big problem. This adversely affects the performance of any models that the Data Science team builds and even effects just basic analysis. This also provides problems for stylists because they use these attributes in searching. Without the attributes, this leaves the stylists spending more time searching for whatever specific item they’re looking for. This issue also leads to weird biases and stock usage. If a shirt is missing its colour (the colour being one of its attributes) and someone was searching for a blue shirt, they’ll never find what they’re looking for. This will result in weird stock usage as the shirt will be used less than it otherwise would be. Outfittery had previously tried to predict missing attributes using just other attributes so in the case of the shirt, you’d have the category it belongs to, material etc. and would use these attributes to try and predict the missing attribute, so in this example: colour. But, Outfittery found they had little success with this. As it turns out: Outfittery tried using a few different formulations using images Firstly, Outfittery tried using a standard convolutional neural network - they fed the full image through the network and tuned it for every separate attribute. However: This resulted in poor performance, mainly due to the lack of data. Following on from the failure in this formulation, Outfittery tried fitting an autoencoder to all the data at first, encoding it and then using these encodings to predict any missing attributes. They found they had more success with this approach. Conor explains that in theory, you would expect that using a full image and a much more complex convolutional neural network would actually produce better results as it can capture more of the weird intricacies. This is a prime example of autoencoders enabling you to do a lot more with less data. Outfittery didn’t stop there. The final formulation they tried was by using autoencoded vectors, as well as using other attributes. They used this as a big predictor factor and this ended up giving them the best results. The best of all three had every single attribute and they tried to separate the model for each attribute. This is now what Outfittery have in production. As if that’s not enough: Once you have these encodings, you can do impressive things with basic vector arithmetic Conor stated that one of these things is to get cosine similarity between the encodings, so you can see how similar two embeddings are. Outfittery have expanded on this and built their own item similarity system, where any user can input the unique IDs of any two items that they have or have had in stock and this system can return their similarity. A practical example of this is when stylists are packing outfits and the exact item they want is out of stock, they can recommend replacement items. This means they don’t have to restart the process again with a whole new outfit, just because they’re missing a piece. This is all background to the primary problem that they are trying to solve: how they can use this model to generate recommendations for their customers. One thing that Outfittery look at is a customer’s history, in which they can use this data in the similarity service and then try and recommend the customer similar items. But, this isn’t what customers want from Outfittery. If a customer has kept a blue t-shirt, they don’t want to be consistently sent blue t-shirts, as they want to try and wear something different every day. While people generally like to wear something different every day, they do tend to keep their clothing within the same sort of style. Conor explains that it is difficult to pinpoint exactly what style means. However: Luckily for Outfittery, their entire order history is a set of professionally styled outfits so have lots of different items - they know how a good style fits together. From there, Outfittery have created their wardrobe completer. They’ve built a model which can quantify the style fit of any two items of clothing similar to the similarity service - they can then use this to predict recommendations for customers based on current stock and their kept item history of the style fit. Autoencoders are using the model to figure out other features, like the glasses vector, pocket vector etc. The Data Science team know there’s a lot of information in the computers in these algorithms but are struggling to reach the point where they can extract it all. If you had an artificial neural network trained to predict information, they’d learn a lot, but as mentioned above, there’s no way to extract that information. If we could extract that information, Conor thinks that we could learn something from the machines as humans. This idea could be useful if you have a model to predict GDP really well. You may be able to extract information, learn a lot about what drives GDP and then use this for guiding government policy in the future. As you can see, the future for Machine Learning and autoencoders is exciting as it implements itself into a variety of different industries.
Machine Learning Examples in Social Housing
What if, by the end of this article, you will know how machine learning has been implemented in the social housing sector? Or, even better, an insight into a company that has first-hand experience of working with machine learning models in this sector? By the end of this article, you'll know exactly that - and much more! We recently held a Data World Tour where we travelled to 7 different cities and were host to some amazing speakers, all discussing different topics in Data Science. Floris Hoogenboom and Jan Pel are both Data Scientists from Future Facts and spoke to us as our Amsterdam stop. Both Floris and Jan are working for WoningNet, a party that matches the supply and demand for social housing in the Netherlands. They explain that you have housing corporations in the Netherlands which own the houses and looks after the property. You then have WoningNet which is the party that decides who gets which house. You enrol at WoningNet and after around 12 years, you’re eligible for a house. Floris and Jan both agree that this number isn’t great. What’s more, If you accept a house, you lose this waiting time, so you’re basically stuck in the house for around 12 years. A lot can happen in 12 years. So Floris and Jan both work as part of a team who have set out to optimize this process and have developed a pairwise ranking algorithm to create movement in the social housing market. In their talk, Floris and Jan explain how their algorithm tries to match the right house to the right tenant. To clarify, a pairwise ranking algorithm is a ranking tool used to assign priorities to multiple options available, in the context of Floris and Jan’s talk, the multiple options are houses. The pairwise ranking algorithm is taught to the machine learning model, so it can now rank content. The algorithm is implemented to get insights about customer’s attitudes and obtain feedback to learn about various customers’ perspectives and their decision-making capabilities. They also showed how they used this algorithm to build a graph representing the housing market in Amsterdam, that can be used to help people migrate to a house better suited to their wishes, therefore creating the movement needed in the housing market. Crazy right? I’ve written an overview of their talk for you which explains how they’ve done this. Let’s get into it. There’s a supply and demand in the social housing sector Floris leads the talk, to begin with. He explained that when you look at the social housing markets, you, of course, have a supply with people living there and you have new entrants who don’t have a house yet, creating the demand. If they redistribute a house, say one person decides that they’re going to move out of their house and they’re going to rent or buy in the non-regularised section of the housing market. Then a lot of people become eligible for the house that they’ve moved out of. If some people apply for the house, the person with the longest wait time will be assigned the house. Once that person moves into the house, they lose their waiting time, so are back to 0 years again. Before they can make another move in the market, they must build their waiting time back up. Floris explains that the whole process of the house becoming vacant and rented out again takes 2 months. Furthermore, Floris explains that they see a lot of people in their houses who are currently unhappy. They may have been happy when they originally moved into the house, but as said previously, a lot can happen in 12 years, which means those who are unhappy are now stuck. Several reasons that can result in a person being unhappy in their living situation, such as that they may feel they’re in the wrong neighbourhood, they may have had a family which means the house is now too small etc. If an unhappy person says that they prefer a different house over their own, and there’s someone else who is unhappy who prefers a different house over their own, then there’s a possibility that a cycle can be found in the market. The idea with these cycles is that if everyone were to follow such a cycle, then there will be people that would be able to make their proposed move, which will result in everybody becoming happier in their living situation. This would also mean that we would have a better allocation of houses. Floris says that there’s a whole field of economics studying this. Though this sounds great, there