Simulation Engineer (Python)

We are looking for a Simulation Engineer to build and run the simulation tooling behind slot game mathematics within an iGaming product. You turn mathematical specifications into fast, reproducible, config-driven simulations, validate the results, prepare math validation reports, and support developers and QA during integration and testing. The mathematical model itself is owned by a Game Mathematician you will work with closely. Prior iGaming experience is welcome but not required. Responsibilities - Build and maintain a config-driven simulation framework for slot games: reels /weights, paytables and feature parameters defined in configuration rather than in code. - Make the tooling usable directly by the Game Mathematician, so balancing iterations can be run without engineering involvement. - Run and analyze Monte Carlo simulations to validate RTP, payout distribution, volatility, hit rate and max win frequency, including convergence and confidence intervals. - Prepare math validation reports generated from simulation runs, with reproducible results (seeded runs, versioned configurations) and result export. - Generate the tables, configuration files and exports that accompany the mathematical documentation. - Cross-check simulation results against analytical calculations and simplified known-answer configurations. - Write and maintain tests for payout calculation logic, and regression checks on RTP across configuration changes. - Support developers and QA during integration and testing phases: reconcile differences between the reference simulation and game engine test runs. Optional / Additional Responsibilities - Build visualization and reporting tools for payout distributions. - Set up CI for simulation runs and automated regression on configuration changes. - Participate in the full game lifecycle (from concept to release). Requirements - Strong Python at an engineering level: numpy, vectorization, profiling, working with large data volumes. - Experience building config-driven, reproducible tools rather than one-off scripts, including seeded runs and versioned configurations. - Applied statistics: confidence intervals, convergence, variance, and working with rare events and distribution tails. - Ability to work precisely from a written technical specification, raising ambiguities rather than resolving them independently. - Testing discipline: unit tests on calculation logic, and validation of simulated results against analytical values. - Strong analytical thinking, attention to detail, and ownership of results. Nice to Have - Experience in iGaming or with casino game mathematics. - Background in a domain involving applied probability: quantitative finance, actuarial work, sports betting, computational physics, or operations research. - Performance optimization experience (Numba, Cython, C++ or Rust). - Experience with CI pipelines for computational workloads. - Understanding of compliance and regulatory requirements in iGaming.