Data Scientist

Senior Data Scientist / ML Engineer – Simulation12-month contract | Fully Remote We are working with an innovative technology business developing a digital twin platform for complex organisations. The platform uses real-world operational data and event logs to simulate how organisations operate, allowing businesses to quantify the impact of operational changes before they are made. We are looking for a Senior Data Scientist / ML Engineer to own the simulation and statistical modelling layer of the platform. What you'll do * Design and develop discrete-event and process simulation models in Python. * Develop statistical and ML methods to fit and calibrate models against real operational data. * Use event logs and timestamp data to infer processes, routing, capacity and durations. * Design simulations and experiments to quantify operational changes. * Build production-quality, reusable modelling systems. * Work closely with data engineering and product teams. * Communicate complex modelling outputs clearly to non-technical stakeholders. Must-have * Strong Data Science / ML Engineering experience with production-grade Python. * Hands-on experience with process or discrete-event simulation, stochastic modelling or Operations Research. * Strong statistical modelling skills, including estimation, calibration and validation. * Experience working with real-world operational, event-log or timestamp data. * Strong Python scientific stack: NumPy, SciPy and pandas. * Good software engineering practices, including Git, testing and reproducible development. Nice to haveExperience in complex operational environments such as: * Aviation / airports * Logistics / supply chain * Transportation * Manufacturing * Healthcare * Financial or professional services * Consulting Experience with process mining, queueing theory, Monte Carlo simulation, survival analysis or agent-based simulation would also be valuable. We're particularly interested in candidates who have taken messy operational data, reconstructed how a real-world process works and built a quantitative model that can be used to support business decisions.