Embed with Product Managers, Engineers, and cross-functional business owners to understand product challenges. Identify and size opportunities to improve player experience and business outcomes. Influence Product roadmap and set up operating metrics and targets to measure impact. Analyze player acquisition, engagement, retention, monetization, and lifecycle behavior patterns. Translate business questions into structured analysis and actionable recommendations to inform hypotheses. Design and interpret A/B test learnings. Recommend next iterations. Build reusable analytical assets and contribute to self-service measurement capabilities. Partner with data engineering teams to improve telemetry, data quality, and measurement infrastructure. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. Experience using SQL and Python, R and agentic AI tools. Experience applying experimentation, statistical analysis, forecasting, or product analytics techniques to business problems. Written and verbal communication skills. Ability to work effectively in cross-functional environments.