F1 Data Analytics Intern — On-site Hinwil, Switzerland

Raceforce Global; Zürich; On-site; CHF 34,000 - 44,000; Part time

Job summary

Audi Revolut F1 Team is seeking a motivated student for a hands-on data analytics internship based at Hinwil, Switzerland. You will work alongside experienced professionals on defined projects that support performance analysis and decision-making across car development and race operations.

The role offers exposure to machine learning, statistical modelling and software tooling, with opportunities to contribute to reusable analysis tools and documentation while collaborating in a fast-paced

Qualifications

• Pursuing CS/DS/Engineering degree or related field.
• Proficient in Python; C++ is a plus.
• Basic knowledge of statistics or ML concepts.
• Familiar with OO programming, version control and containerisation.
• Interest in RL, multi-agent systems or CV is advantageous.
• Strong analytical and problem-solving skills.
• Good communication and teamwork abilities.

Responsibilities

• Assist with daily data analytics activities within Digital Solutions.
• Help develop and test machine learning models.
• Support statistical and simulation-based analyses.
• Package, deploy and maintain reusable analysis tools.
• Contribute to code reviews, testing and documentation.
• Conduct research and analysis as required.
• Collaborate with team members in technical meetings.
• Present findings and contribute to reports.

Skills

Python

C++

Statistics

Version control

Containerisation

Analytical thinking

Communication

Teamwork

Education

CS/DS/Engineering student

Tools

Git

Docker

CI/CD basics

Job description

Audi Revolut F1 Team is seeking a motivated student for a hands-on data analytics internship based at Hinwil, Switzerland. You will work alongside experienced professionals on defined projects that support performance analysis and decision-making across car development and race operations.

The role offers exposure to machine learning, statistical modelling and software tooling, with opportunities to contribute to reusable analysis tools and documentation while collaborating in a fast-paced