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F1 Data Scientist

FEDERATION INTERNATIONALE DE L'AUTOMOBILE

Suiza📅 24/9/2026

Descripción

The Data Intelligence Team works alongside different technical groups to lead the data transformation of the department. Our work focuses on designing, building and deploying end to end data solutions that will enable more effective real-time decisions trackside and allow data-driven design of future sporting and technical regulations. We seek result-driven, proactive people, who are passionate about building high-quality software solutions that address problems by transforming how engineers use data and technology. They must have a desire to innovate in a collaborative and fast-paced environment, as part of a growing team pushing the boundaries of what is possible in the unique and inspiring world of Motorsport. The position will be based in our headquarters in Geneva and will involve some travel to Formula 1 championship events. MISSIONS AND RESPONSIBILITIES: As F1 Data Scientist your mission is to design, test and deploy data solutions that transform raw motorsport data into powerful, actionable insights. You will work with large and diverse sources of data including telemetry time series, images or regulatory documents across multiple championships with the aim to build innovative tools and models that enhance understanding, and support fast decision-making. To accomplish this, you will be part of the end-to-end product life-cycle: from requirement gathering and PoC development to deployment of production-ready solutions designed to scale, be understood by end users, meet organisation requirements and adapt as needs evolve. This role is ideal for someone who takes initiative, owns their work end-to-end, and actively contributes to a high-performing team. Data Science Develop Machine Learning models and advanced analytical tools that can provide further insights for decision-making. Further develop the FIA data analytics tool suite to optimise our remote and on-track support operations through real time analysis. Investigate multimodal approaches that integrate t
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