Data Science Engineer

Aston Martin F1
Towcester
1 week ago
Create job alert
Data Science Engineer

Application Deadline: 27 March 2026

Department: Vehicle Science

Employment Type: Permanent - Full Time

Location: Silverstone

Reporting To: Robbie Stevens

Description

Are you passionate about applying advanced modelling and AI to unlock performance in one of the most cutting edge engineering environments in the world? Join our Vehicle Science team as a Data Science Engineer, where your work will directly influence and continuously improve the performance of our Formula One car.

This is a unique opportunity to use mathematical modelling, physics based methods, and machine learning to accelerate simulation, improve predictive capabilities, and generate high value insights across aerodynamics and other engineering domains.

Key Responsibilities

In this role, you'll be at the forefront of data driven performance engineering. You will:

  • Build robust, reliable data driven and physics informed models using advanced mathematical and AI/ML methods.
  • Develop and optimise scalable data pipelines integrating simulation data, physical testing outputs, and trackside measurements.
  • Research and implement state-of-the-art AI/ML techniques to improve modelling fidelity and computational speed.
  • Collaborate with Aerodynamics, Vehicle Performance, Simulation & Modelling and other technical groups to embed insights into engineering decisions.
  • Communicate findings through clear reports, visualisations, and presentations for both technical and nontechnical audiences.
  • Ensure data quality, security, and compliance across the modelling workflow.
  • Write clean, maintainable code using modern software engineering practices and AI assisted development tools.
Skills, Knowledge and Expertise

We’re looking for someone analytical, curious, and ready to push boundaries. You should have:

  • A master's degree or higher in Mathematics, Physics, Engineering, Computer Science or a related field.
  • Strong understanding of reduced order modelling and ideally exposure to fluid mechanics or other complex physical systems.
  • Excellent analytical skills across experimental methods, modelling, statistical inference, and data driven techniques.
  • Familiarity with surrogate modelling, emulators, and predictive algorithms used to accelerate engineering workflows.
  • Preferably, strong programming skills in Python and experience with ML/scientific libraries such as SciKitLearn, JAX or PyTorch. However, software training will also be provided.
  • Ability to work calmly under pressure, manage competing priorities, and deliver high-quality results on tight timelines.
  • Strong problem-solving ability and confidence making data driven recommendations.
  • A collaborative mindset and enthusiasm for building strong working relationships across teams.
Benefits

Investing in your career is paramount. We promote professional and personal development through a provision of learning opportunities and work with you to shape your career and realise your full potential.

As part of our high-performing, collaborative team, you'll enjoy a competitive package, including a discretionary bonus scheme, private healthcare, pension plan, life assurance, TEDSgroup childcare benefits, a cycle-to-work scheme, tech scheme, and car scheme.

You will also have access to our state-of-the-art facilities at the AMR Technology Campus, featuring a new on-site gym with fitness, spin and yoga classes, a bistro café, and restaurant.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Engineer Global Digital Media/MarTech

Data Science Engineer Intern — Summer 2026

Data Science Engineer

Data Science Engineer: Growth & Revenue Modeling

Data Science Engineer – High-Performance Vehicle AI

Data Science Engineering Manager – Audit (Hybrid)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.