Machine Learning Research Scientist, Player Modeling
Core
Develop mathematical and ML models for player behavior, game mechanics, and regulatory compliance in casino and slot machine games.
Role type
Senior Machine Learning Research Scientist (Player Modeling)
Builds
Predictive models of player engagement/monetization, core mathematical models for slot machines, and regulatory certification reports.
Domain
Gaming industry + Probability theory & Combinatorics
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Combinatorics, Probability theory, Statistics, Mathematical modeling for game design, Data intuition (distribution shift/leakage), Software engineering fundamentals, Python programming, Simulation tools, Regulatory compliance knowledge
Preferred skills
Experience with gradient boosting, reinforcement learning, bandits, constrained optimization, AWS, MATLAB, R
Technologies
AWS, Python, MATLAB, R, Cloud
Responsibilities
Translate product questions into modeling problems using probabilistic and generative models; Build and refine core mathematical models for slot machines to achieve target RTP and volatility; Design and validate random mechanics and bonus rounds through combinatorial reasoning; Work with large, imbalanced datasets to diagnose data quality and design evaluations; Perform large-scale simulations to forecast game performance; Productionize models with reproducible code and build ML pipelines on AWS; Prepare mathematical models and reports for certification with global regulators (GLI, BMM); Play-test games and analyze live performance data.
Seniority
Senior, hands-on IC