Data Science Engineer – Vehicle Science
Summary
Data Science Engineer on Aston Martin Aramco F1's Vehicle Science team in Silverstone, building mathematical, physics-based and machine-learning models to accelerate simulation and improve aerodynamic performance using CFD, wind tunnel and track data. Core stack is Python with scientific computing and ML libraries like scikit-learn, JAX or PyTorch.
Are you passionate about applying advanced modelling and AI to unlock performance in one of the world's most demanding engineering environments? Join our Vehicle Science team as a Data Science Engineer, where your work will directly influence the development and performance of our Formula One car.
- Develop and maintain robust mathematical, physics-based and data-driven models to improve engineering analysis and aerodynamic performance.
- Design and optimise scalable data pipelines integrating complex datasets from CFD, wind tunnel testing, track activities and other engineering sources.
- Research and apply advanced AI and machine-learning techniques, including surrogate models, emulators and reduced-order methods, to improve predictive capability and accelerate simulation.
- Collaborate with Vehicle Science, Simulation and Modelling, Aerodynamics, Vehicle Performance and other technical groups to embed modelling insights into engineering workflows and decisions.
- Analyse complex datasets, evaluate model performance and communicate findings through clear technical reports, visualisations and presentations.
- Maintain high standards of data quality, integrity, security and traceability across modelling workflows.
- Write clean, efficient and maintainable code using sound software engineering practices, version control and AI-assisted development tools where appropriate.
- Master's degree or higher in Mathematics, Physics, Engineering, Computer Science or another relevant scientific or computational discipline.
- Strong knowledge of mathematical and data-driven modelling, including reduced-order modelling, surrogate models, emulators and predictive algorithms.
- Strong analytical skills across modelling, experimental methods, statistical inference and data analysis; experience with fluid mechanics or other complex physical systems is advantageous.
- Excellent programming skills in Python, with experience using scientific computing and machine-learning libraries such as scikit-learn, JAX or PyTorch. Further software training will be available where required.
- Ability to evaluate models, investigate unexpected results and draw robust, evidence-based conclusions from complex engineering data.
- A proactive, results-oriented approach, with sound technical judgement and the ability to manage competing priorities under pressure.
- Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary engineering teams.
Make an impact
At Aston Martin Aramco, the way we model, simulate and interpret engineering data can make a real difference to car development. You'll help advance the tools and techniques that enable our engineers to extract greater value from simulation, wind tunnel and track data, improve predictive understanding and make better-informed decisions.