Data Scientist, Portfolio Analytics

What you will do

• Analyze, model, and interpret extensive datasets representing millions of players to uncover trends and insights that answer both strategic and operational questions.
• Implement advanced statistical and machine learning techniques to provide deeper insights, continuously improving the team’s analytical capabilities.
• Develop predictive models and algorithms to forecast player behaviors, retention, and revenue potential, empowering teams to make data-driven optimizations.
• Identify patterns and commonalities across the game portfolio that can guide recommended approaches and strategic alignment.
• Define and improve critical metrics, frameworks, and tools that help teams understand player lifecycle and optimize LTV, loyalty, and retention.

What we're looking for

• Solid experience in data science, with a background in statistical analysis, predictive modeling, and machine learning in a business context, ideally for 3+ years.
• Proficiency in SQL and programming languages such as Python or R; experience with large datasets and big data tools (BigQuery or similar) is a plus.
• Experience with visualization tools (Looker, Tableau, or QlikView) to build compelling data stories that communicate insights effectively.
• Strong ability to translate data insights into strategic recommendations that align with business objectives.
• Skilled in presenting complex results to stakeholders, ensuring insights are understood and actionable across teams

Bonus points

• Master’s degree or equivalent experience in a quantitative field (e.g., Data Science, Statistics, Economics, Computer Science, Engineering, or a related field).
• Familiarity with or experience in the gaming industry, along with a passion for understanding player motivations and game design.