Graduate Data Scientist - Vehicle Science
Summary
Graduate data scientist on the Aston Martin Aramco Formula 1 team's Vehicle Science group: building physics-based, reduced-order and machine-learning models plus Python analysis tools over simulation, wind tunnel and track data to help engineers improve car performance.
You'll work with data from simulation, wind tunnel testing and the track, developing practical models and analysis tools that help our engineers understand vehicle behaviour, identify trends and make better-informed decisions. Working alongside experienced specialists, you'll build your technical expertise while contributing to the engineering work that drives car development.
- Develop and improve physics-based, reduced-order and data-driven models to support engineering analysis and vehicle performance decisions.
- Build and maintain Python analysis tools to turn simulation, wind tunnel and track data into meaningful engineering insight.
- Undertake modelling tasks from problem definition and data preparation through to development, verification, validation and documentation, with guidance from experienced colleagues.
- Apply mathematical modelling, statistics and machine-learning techniques to identify trends, improve predictions and accelerate engineering workflows.
- Help integrate data from multiple sources and contribute to reliable data pipelines, shared modelling tools and datasets.
- Collaborate with Vehicle Science, Simulation and Modelling, Aerodynamics, Vehicle Performance and other engineering teams to understand problems and develop practical solutions.
- Communicate findings through clear reports, visualisations and presentations, while maintaining good coding practices, testing, version control and documentation.
- BSc or MSc in Mathematics, Applied Mathematics, Physics, Engineering, Computer Science or another relevant quantitative discipline.
- A sound understanding of mathematical modelling, statistics and data analysis, with an interest in applying these to complex engineering problems.
- Knowledge of regression, optimisation and machine-learning methods; familiarity with surrogate or reduced-order modelling would be advantageous.
- Programming experience in Python, ideally using libraries such as NumPy, pandas, SciPy and scikit-learn.
- Understanding of model validation, uncertainty and error analysis, with the ability to investigate unexpected results and draw evidence-based conclusions.
- Strong analytical and problem-solving skills, curiosity and a willingness to learn, with the ability to communicate findings clearly.
- A collaborative, proactive approach, with the ability to manage priorities and deliver work to demanding timescales.
Make an impact
At Aston Martin Aramco, data science is an important part of understanding and improving car performance. You'll have the opportunity to apply your mathematical and programming skills to real engineering problems, helping our engineers extract greater value from simulation, wind tunnel and track data.
