WE SPECIALISE IN FINDING FANTASTIC OPPORTUNITIES
FOR DIGITAL AND DATA SPECIALISTS WITH THE MOST INNOVATIVE BUSINESS ACROSS EUROPE AND THE USA.
San Francisco, California
7 months ago
Darwin Recruitment has partnered with a highly driven, well-funded start-up located in San Francisco that's focused on making high-quality healthcare services available to everyone.
This company is made up of interdisciplinary thinkers who are passionate about technology and medicine. Their vision goes much further than building a state of the art diagnostic engine that gains knowledge from all of the global leaders within the radiology space… Through their end to end workflow, they believe that enabling diagnosticians is just the start.
Ultimately, their mission is to improve the quality and efficiency of the entire episode of care, simplifying the process of medicine and allowing doctors to focus on patients.
Here's what their Head of Data Science said, "This is by far the hardest technical work that I've been involved with. The daily challenges are extremely complex but they're very interesting and highly rewarding. So if we meet a candidate for any of our open role's that enjoys being tested technically, then this is the kind of environment that they will thrive in"
What are they Looking for?
Someone who will be ultimately responsible for the technological foundations of their product. This Senior NLP Data scientists will define and implement strategies to handle free-form medical text, including developing internal NLP packages and/or heavily customizing open-source solutions. They will contribute to the development of ontologies and associated biomedical tooling, and support various other data science initiatives.
Here's what's needed to be considered?
- PhD or a similar advanced degree in computational linguistics, informatics, or related field
- Published academic work in core NLP disciplines and/or open-source NLP software contributions
- Experience working with medical and/or radiological text data
- Experience building and using ontologies and knowledge graphs to support natural language processing, data integration and analytics
- Deep understanding of core NLP/NLU algorithms, tasks, model architectures, and open-source resources: CRFs, Neural Networks (LSTMs, dense vector embeddings), rules-based/regex approaches. Named Entity Recognition and Disambiguation, POS tagging, syntactic dependency parsing. spaCy, gensim, NLTK, StanfordNLP, annotation tools (e.g. Brat, Daccano)
- Expert coding ability (Ideally Python)
- Proficiency with RDF, OWL, SPARQL or similar technologies
- Familiarity with key biomedical informatics resources (e.g. UMLS, SnoMed, BioPortal, Radlex)
- Experience leading/growing and mentoring teams