Responsibilities:

• Build and evaluate predictive and decision models to be deployed in production systems, or for research


• Analysis of large amounts of historical data, determining suitability for modeling, data clean-up and filtering, pattern identification and variable creation, selection of sampling criteria, generating performance definitions and variables


• Conducting experiments with different types of algorithms and models, analyzing performance, to identify the best algorithms to employ.


• Architect and develop operational models that run at scale thru partnership with data engineer teams

Required Technical and Professional Expertise

• 6+ years of industry work experience in data scientist projects


• Master’s degree or higher in Statistics/Math/Computer Science or related field


• Background in applied statistical modeling on large experimental or observational data sets


• Experience extracting data from a variety of sources, and a desire to expand those skills (working knowledge SQL is required, Spark is a plus)


• Experience with one or more statistical or machine learning software such as R, Python, etc.


• Must showcase past work through published articles/GitHub/social media

Preferred Technical and Professional Expertise

• Knowledge of distributed computing systems, e.g. Cosmos, Spark, Hadoop, and relational database management system


• PhD. in Statistics is preferred


• You love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies


• Ambitious individual who can work under their own direction towards agreed targets/goals and with creative approach to work


• Intuitive individual with an ability to manage change and proven time management


• Proven interpersonal skills while contributing to team effort by accomplishing related results as needed


• Up-to-date technical knowledge by attending educational workshops, reviewing publications