Simulation Engineer (Python) (Game Math)

We are looking for a Simulation Engineer to build and maintain the simulation tooling behind slot game mathematics within an iGaming product.

You will turn mathematical specifications into fast, reproducible, configuration-driven simulations, run large-scale Monte Carlo simulations, validate game mathematics, and prepare reports and datasets used throughout the game development process.

You will work closely with a Game Mathematician, who owns the mathematical model. Your role is to turn those specifications into reliable simulation tools and ensure that the results are accurate, reproducible, and ready to be used by developers, QA, and the wider game team.

Prior experience with slot games or iGaming is welcome, but not required. We are also open to engineers with strong experience in applied probability, statistics, quantitative modelling, or other computational domains.

What You’ll Do

Build and maintain a configuration-driven simulation framework for slot games, with reels, weights, paytables, and feature parameters defined through configuration rather than hard-coded logic.

Make the simulation tooling accessible to Game Mathematicians, allowing them to run balancing iterations and test different configurations without engineering involvement.

Run and analyse large-scale Monte Carlo simulations to validate key game metrics, including RTP, payout distribution, volatility, hit rate, and maximum-win frequency.

Analyse simulation convergence, confidence intervals, variance, and rare-event distributions to ensure statistically reliable results.

Build reproducible simulation workflows, including seeded runs, versioned configurations, and exportable results.

Generate tables, configuration files, datasets, and other outputs required for mathematical documentation and game validation.

Prepare math validation reports based on simulation results.

Cross-check simulation outputs against analytical calculations and simplified known-answer configurations.

Develop and maintain unit and regression tests for payout calculation logic and RTP across configuration changes.

Support developers and QA during integration and testing by investigating and reconciling differences between the reference simulation and the production game engine.

Contribute to improving the performance, reliability, and usability of the simulation framework.

Additional Opportunities

Depending on your experience and interests, you may also:

Build visualisation and reporting tools for payout distributions and simulation results.

Set up CI pipelines for automated simulation runs and regression testing.

Optimise computationally intensive workloads using technologies such as Numba, Cython, C++, or Rust.

Participate in the full slot game lifecycle, from mathematical concept and balancing through development, testing, and release.

What We’re Looking For

Strong Python engineering skills, including NumPy, vectorisation, profiling, and processing large volumes of data.

Experience building reliable, reusable, configuration-driven tools rather than one-off scripts.

Understanding of reproducible computational workflows, including seeded simulations and versioned configurations.

Strong knowledge of applied statistics, including confidence intervals, convergence, variance, distributions, and rare events.

Ability to work precisely from a written mathematical or technical specification and proactively identify ambiguities or missing requirements.

Strong testing discipline, including unit testing of calculation logic and validation of simulated results against analytical or known-answer values.

Strong analytical thinking and attention to detail, particularly when working with probabilistic models and large simulation datasets.

Ability to take ownership of simulation accuracy and the reliability of results.

Comfortable working closely with mathematicians, developers, and QA engineers.

Nice to Have

Experience with iGaming, online casino, slot games, or game mathematics.

Experience working with reels, paytables, RTP, volatility, hit rates, bonus features, or other slot-game mechanics.

Background in a domain involving applied probability, statistics, or computational modelling, such as quantitative finance, actuarial science, sports betting, computational physics, or operations research.

Experience with Numba, Cython, C++, or Rust for performance optimisation.

Experience building CI pipelines for computational or simulation workloads.

Understanding of iGaming compliance and regulatory requirements.

Tech Stack

Python · NumPy · Monte Carlo Simulation · Applied Statistics · Configuration-driven Systems · Automated Testing · CI/CD

Nice to have: Numba · Cython · C++ · Rust · Data Visualisation