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.