Principal Data Scientist - Product Analytics - XBOX Growth

XBOX Growth Intelligence is seeking a Principal Data Scientist, Product Analytics to set analytics strategy and partner with Product, Engineering, and Business leaders across XBOX product experiences. This role will lead ambiguous, organization-level problems; translate player and business signals into investment choices; and establish scalable measurement approaches that accelerate decision-making across teams. The ideal candidate combines deep scientific rigor, product judgment, and the ability to align senior leaders and drive durable business impact through others. 

In this role, you will help Product, Engineering, and Business leaders use shared metrics and evidence to prioritize portfolio investments and make cross-product tradeoffs. You will apply analytics and scientific methods to drive measurable improvements in DAU, retention, engagement, monetization, and other business outcomes, while building reusable frameworks, AI-enabled capabilities, and measurement standards that improve rigor, scalability, and decision velocity across teams. As a trusted strategic advisor and scientific leader, you will help shape product direction and elevate analytics capabilities across the broader organization.

• Lead product analytics strategy across multiple XBOX product areas spanning Console, PC, Store, and Platform experiences, serving as a strategic advisor to senior Product, Engineering, and Business leaders. 

• Establish organization-level success metrics, operational targets, measurement frameworks, and leading indicators that align teams and guide portfolio investment decisions. 

• Identify and size growth opportunities through advanced analytics and machine-learning models across player acquisition, engagement, retention, monetization, and lifecycle behaviors. Anticipate risks, synthesize cross-product insights, and shape roadmap and investment tradeoffs. 

• Set methodological direction for experimentation, causal inference, and incrementality measurement; lead rigorous reviews to ensure approaches are robust, unbiased, scalable, and decision-ready. 

• Lead development of reusable analytical assets, agentic AI workflows, and self-service capabilities that can be adopted across product areas and materially improve decision velocity. 

• Drive cross-organizational alignment with Data Engineering and Software Engineering to strengthen telemetry, data quality, and scalable, resilient measurement infrastructure. 

• Raise the scientific and product analytics bar by mentoring data scientists, reviewing complex work, and establishing standards and reusable practices across the organization. 

Required Qualifications 

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.

Preferred Qualifications: 

• Expertise in SQL, Python or R and agentic AI tools. 

• Expertise applying product analytics, experimentation, causal inference, statistical analysis, forecasting, and data storytelling to solve highly complex problems and drive measurable business impact across multiple product areas. 

• Executive communication skills, with a track record of turning ambiguous business questions and technical tradeoffs into clear recommendations, decision frameworks, and aligned action. 

• Demonstrated ability to influence senior leaders across functions, resolve competing priorities, and drive organization-level decisions through data and scientific judgment. 

• Demonstrated technical and methodological leadership, including setting standards, reviewing complex work, mentoring others, and leading through influence.

   

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