Senior Data Scientist - Experimentation & Measurement San Mateo, CA
Overview: As a Senior Data Scientist on the Decision Science team within the Data Science, Analytics, & Enablement (DSAE) organization at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of PS4 to PS5 user migration initiatives, growth marketing strategies, and broader campaign performance. This role is focused on advancing our experimentation practices-bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across PlayStation.
What You'll Be Doing: Lead the design, execution, and interpretation of A/B tests and quasi-experiments to evaluate the impact of user migration initiatives (PS4 to PS5), growth marketing strategies, and campaign performance.
Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles.
Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication.
Apply advanced causal inference methods when experimentation isn't feasible or to inform test design and prioritization.
Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company.
Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools.
Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity.
Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team's work.
Basic Requirements: Master's or PhD in Statistics, Economics, or Econometrics. Other degrees in quantitative disciplines may be considered.
5+ years of experience in a data science experimentation-focused role (3+ with PhD).
Deep expertise in A/B testing and causal inference, including quasi-experimental methods.
Proficiency in SQL for data extraction and transformation.
Proficiency in Python, including statistical and data science libraries.
Broad and applied knowledge of statistical techniques and machine learning modeling methods.
Proven ability to influence product and business decisions through clear, actionable insights.
Experience contributing to or developing experimentation frameworks, best practices, or internal tooling.
Bonus: Interest in or knowledge of video games, gaming platforms, or player behavior.