What We Need

We seek a Sr Data Scientist to join the experimentation and causal inference team that supports 2K sports games, including NBA2K, WWE 2K, PGA 2K, Lego Drive, and more! Lead data authority who contributes directly to driving the research direction in developing methods and tools that increase the difficulty and efficiency of our experimentation platform and analyses constructed using causal inference techniques. Partner with studio and product leadership to help them understand the true impact of the decisions and tests.

What You Will Do

• Effectively identify and apply analytics, causal inference, experimentation, and machine learning techniques for business problems.
• Significant experience and excitement with one or more of the following: advanced statistical techniques for A/B testing, methods for experimental design, observational causal inference, or quasi-experimental analysis.
• Examples include quantile testing, sequential testing, variance reduction techniques, variance estimation for ratio metrics, multi-level/hierarchical modeling, statistical surrogate modeling, matching methods, regression adjustment, structural equation models, instrumental variables, regression discontinuity design, and graphical approaches to causal inference.
• Lead the design, analysis, and interpretation of experiments
• Proactively perform data exploration on engagement behaviors to discover future opportunities.
• Partner/influence directly with and regularly present insights to key strategic business partners (e.g., Growth Strategy, Marketing, Product Development)
• Up-level others on the team through mentorship and peer review using your experience and domain expertise.
  
  

Who We Believe Will Be An Outstanding Fit

• 5+ years work experience in data science with a Master or PhD degree in Mathematics, Statistics, Economics, Computer Science, Engineering Sciences (or in another quantitative field)
• 5+ years of professional experience with data scripting languages (SQL, python, R, etc.)
• In depth understanding and experience using supervised and unsupervised machine learning techniques
• Solid understanding of causal inference methods (such as propensity score matching, synthetic control methods, etc.)
• You are a creative problem solver, a self-starter with the passion and enthusiasm to drive impact and build whatever is necessary.
• You can optimally balance problem-solving from a technical solution standpoint while providing transparency through concise partner communications.
• Experience in applying statistical analysis, machine learning, and experimentation design within a consumer-facing business
  
  

Bonus Points

• Experience in building experimentation platforms and causal inference solutions
• Familiarity with software engineering practice and working with APIs