Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist

Alpine
Chipping Norton
3 weeks ago
Create job alert
Overview

We’re on a mission to return to the front of the grid. We are looking to reinforce our Data Science team here in Enstone and work towards investigation, development, implementation, and maintenance of data models and services in close collaboration with different departments.


This role is for a Data Scientist to join the Software Engineering & Data team, where you will play a crucial role in developing cutting-edge solutions to help the team achieve our goals in the Formula One World Championship.


The Role

This is a unique opportunity to be part of a Data Science team, working together with Software and Platform Engineers who work tirelessly to improve all areas of the team, from the design and manufacture of the car to the performance analysis at track. The role covers both scientific and engineering aspects of Data Science. The ideal candidate will have passion for data, knowledge sharing and collaboration.


You will be responsible for proposing, developing, implementing/delivering, and maintaining machine learning based solutions for complex F1 problems, as well as communicating with the engineering teams to analyse problems and develop solutions. The ideal candidate will have experience in Data Science algorithms, with demonstrated ability to work and deliver results autonomously within tight schedules.


The Person

If you have a BSc or MSc degree in a relevant field for Data Science, have more than 2-year experience of development in Python and machine learning techniques in production or laboratory, and understand the key parameters that affect their performance as well as end to end data science pipeline, we would love to hear from you!


We are looking for individuals with excellent verbal and written communication and a strong troubleshooting and problem-solving skills.


We Are Looking For Knowledge And Expertise Of

  • Python data science packages: Pandas, numpy, scikit-learn, pytorch…
  • Machine Learning techniques: Neural Networks, XGBoost, …
  • Pipelines and deployment technologies: Azure DevOps, docker, GitHub actions, …
  • A good understanding of architecture and design patterns
  • Committed to deadlines
  • Willing to work in a fast-paced environment as part of a strong-cultured team

Other skills that, although not required, will be considered advantageous would be a good level of general programming in other relevant languages (e.g. Rust, C#, …).


Positive/“can do” work attitude is of high value for this role. We are looking for a team player with passion for investigation and knowledge sharing.


Not only is this a fantastic role, but it is also a fantastic team to work with here in Enstone at a very interesting point in our journey. A good salary is just the start, there are many other benefits too such as our bonus scheme, private health care cover, company contributed pension scheme, on site gym, subsidised canteen, and a car scheme.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.