Data Strategy & Insights Student Placement (Powertrains)

Red Bull; Milton Keynes; On-site; GBP 19,000 - 23,000; Part time

Benefits offered by this job

Bonus scheme

Private healthcare

Pension scheme

On-site gym

Free daily food allowance

Job summary

Red Bull Powertrains invites applications for a Data Strategy & Insights Student Placement (Powertrains) in Milton Keynes. You will join the Data Strategy & Insights team for a year, turning Power Unit data into insights that inform performance and reliability, and building dashboards and models.

We seek undergraduates with interest in data analysis, statistics, ML, and data viz, ready to contribute to cross-disciplinary projects across engineering and trackside teams during the 2027 season and

Qualifications

• Knowledge and experience from at least one year of undergraduate study in a STEM field.
• Strong understanding of statistical/analytical methods with real-world applications.
• Proficiency in Python/SQL/MATLAB or similar for data analysis and modelling.

Responsibilities

• Analyse large-scale Power Unit datasets to extract insights and detect anomalies.
• Support development of statistical and ML models for reliability prediction and fault detection.
• Contribute to exploratory data analysis on trends across tests and races.
• Build and maintain dashboards, reporting tools and automated analytics workflows.
• Support KPI definition and monitoring across the Power Unit function.
• Contribute to data quality checks and validation for critical datasets.
• Report insights through visualisation and technical documentation to stakeholders.
• Collaborate with engineering and trackside teams to deliver data-driven solutions.
• Gain exposure to the 2027 Formula 1 season and future RB Powertrains initiatives.

Skills

Python

SQL

Data analysis

Power BI

Visualization

Statistical modeling

Education

STEM degree (math/stats/data science/engineering/physics)

Tools

MATLAB

Power BI

Tableau

SQL

Job description

Data Strategy & Insights Student Placement (Powertrains)

2026-09-08T00:00:00

Milton Keynes

Buckinghamshire

GB

MK9 3

Any

2026-12-07T15:58:02.423

Red Bull Powertrains are offering a year-long placement opportunity within our Data Strategy & Insights team. In this hands-on role you will be immersed into the heart of our state-of-the-art Technical and Testing facilities, turning Power Unit data into the insight that drives on-track performance and reliability. Pushing boundaries is in our DNA! We're looking for individuals with a strong interest in areas such as data analysis, statistical modelling, machine learning, data visualisation, and reporting automation. This placement offers the opportunity to work across a broad range of disciplines including data science, mathematics, statistics, and engineering, while gaining hands-on experience analysing Power Unit data, building dashboards and models, and delivering insight that informs performance, reliability and operational decisions.

Your responsibilities will include:

• Analyse large-scale Power Unit datasets to extract performance insights and detect anomalies, working closely with engineering and trackside teams
• Support the development and application of statistical and machine learning models for reliability prediction and fault detection
• Contribute to exploratory data analysis on long-term trends across tests and race events
• Help build and maintain dashboards, reporting tools and automated analytics workflows
• Support the definition and monitoring of KPIs across the Power Unit function
• Contribute to data quality checks and validation routines to ensure accuracy and consistency in critical datasets
• Interpret and report data through clear visualisation and technical documentation, presenting insights to both technical and non-technical stakeholders
• Collaborate closely with engineering, trackside and operational teams to deliver world-class data-driven solutions
• Gain direct exposure to the 2027 Formula 1 season and contribute to the future of Red Bull Powertrains

We're looking for passionate, curious, and driven undergraduates who are eager to turn data into decisions in a fast-paced, high-performance environment. If you're ready to take on real responsibility, solve real-world engineering challenges through data, and contribute to the future of Red Bull Racing's success on track, this is your opportunity.

Expected knowledge, experience & attributes of the successful candidates:

• Knowledge and experience from at least one year of undergraduate study on a mathematics, statistics, data science, engineering, physics or related STEM degree course
• A solid understanding of statistical and analytical methods, with the ability to apply them to real-world engineering problems
• Knowledge of Python, SQL, MATLAB, or similar for data analysis and modelling
• Experience with data visualisation tools such as Power BI, Tableau or similar (preferred)
• Experience handling and analysing large or complex datasets and confidence in preparing high-quality technical documentation
• Ability to break complex technical problems down to fundamental principles and derive actionable insight
• Ability to demonstrate a genuine passion for data science or analytics through involvement in extra-curricular projects, previous placements, or work experience
• Positive, can-do attitude and willingness to learn new skills
• Ability to follow best practice and work on multiple tasks simultaneously
• Excellent communication skills and experience working in a team environment

The placement will be for 1 year, starting July 2027.

At Red Bull Powertrains, we believe that success isn't just about speed, it's about the team behind the victory. We trust, support, and challenge each other, always pushing for better. If you love solving complex problems, thinking fast, and making a real impact, this is the place for you.

Alongside a competitive salary, you'll enjoy:

• Bonus scheme
• Private healthcare
• A pension scheme
• On-site gym
• Free daily food allowance
• And many more!

Most importantly, you'll play a key role in powering championship-winning cars.