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.