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.