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Data Scientist - Fraud Detection

  • Location

    Dallas, Texas

  • Sector:

    Cyber Security, Data Science

  • Job type:


  • Salary:

    US$150000.00 - US$200000.00 per annum + Fantastic Comp package available

  • Contact:

    Lewis Adams-Dunstan

  • Email:


  • Job ref:

    JN -022019-82592_1549922340

  • Published:

    almost 2 years ago

  • Expiry date:


  • Startdate:


  • Consultant:


Data Scientist- Dallas, TX

About the Role:

My client is currently looking for a Data Scientist to join their Dallas team. They are looking for innovative, action-oriented professionals with the desire and initiative to make a major impact on the mobile and ad-tech markets.

You will be a key member of the Research and Technology team; you'll very quickly take the lead on defining, prototyping, and ultimately shipping product features. You'll need to develop good intuitions about what will be meaningful to their customers as well as the fastest way to execute, as you partner with all pillars of thier business. You will utilize and implement a wide variety of machine learning algorithms and write robust, production-level code. In this role, you'll be constantly learning, constantly teaching, and always ready to engage in the careful details as well the big picture of what data reveals about the world.

About the Team:

The work environment is collaborative, fast-paced and team-driven. Become a valuable contributor to a transformative business that is just as passionate about its employees as its clients.

What to expect:

* A dynamic role with a diverse set of customers, various industry domains, and challenging solutions

* Flat organizational structure with significant opportunity for advancement and leadership

* Open culture where commitment, respect, and open communication are essential

* Perfect balance of creativity, innovation, analytical thinking, and rolled-up sleeves


You have strong programming skills and strong understanding of applied data science. You will work in a highly collaborative environment where you communicate and plan tasks and ideas.

· Ability to work in fast-paced environment, quickly iterating on a minimum viable solution

· Hands-on experience working with large volumes of geospatial data

· Good understanding of big data application stack, Spark/Hadoop

· Excellent knowledge of efficient and optimized SQL queries

· Perfect verbal and written communicator explaining complex technical concepts in plain language

· Hands-on experience with Agile Software Development practices, including JIRA, version control, release cycles, etc.

· Ability to write production ready code base with minimal supervision

· Strong understanding of research process and produce high quality documentation for internal and external users

· Educate non-technical audience on methods and techniques used when building solutions

· Top-down thinker, excellent communicator, and great problem solver


The ideal candidate has a background in distributed applications, data warehousing and databases, and machine learning concepts. The candidate is highly proficient in big data ecosystem Spark/Hadoop. The candidate has strong programming skills in Scala/Java, Python, SQL and has an expertise in statistical algorithms for data analysis.

· More than 2-years of experience in Data sciences or Master's in mathematics, statistics computer science, or related.

* Hands on experience in machine learning, sampling, feature engineering features

* Proven experience writing production-grade software/algorithms/models

* Strong experience in supervised and unsupervised learning

* Great understanding of time-series analysis and anomaly detection

* Cloud hosting experience AWS, Azure, Google, Databricks

* Adtech industry expertise

* Experience with building solutions for identifying fraud and invalid traffic within adtech ecosystem

* Hands-on experience with Databricks and Spark SQL

* Hands-one experience with Scikit-learn, Spark ML/MLlib and Pyspark, TensorFlow, etc.

* Strong understanding of Machine Learning workflow and development cycle