Description
The Data Intelligence Team at FIA works alongside different technical groups to lead the data transformation of the department. We focus on designing, building, and deploying end-to-end data solutions that 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. The position will be based in our headquarters in Geneva and will involve some travel to Formula 1 championship events.
Job 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 of building innovative tools and models that enhance understanding and support fast decision-making.
Your responsibilities include:
- Developing Machine Learning models and advanced analytical tools that provide further insights for decision-making.
- Further developing the FIA data analytics tool suite to optimise remote and on-track support operations through real-time analysis.
- Investigating multimodal approaches that integrate telemetry time series, image, video, audio, and regulatory documents to enrich analytical capabilities.
- Building and maintaining robust MLOps solutions to ensure scalability, reliability, and continuous improvement of deployed solutions.
- Collaborating with the Data Intelligence group to standardize data processing and promote shared tools across different FIA championships.
- Staying up-to-date with state-of-the-art models, especially in time series treatment and multimodality areas.
- Staying updated on MLOps tools, techniques, and best practices to enhance team capabilities.
Requirements:
- Master's degree or equivalent working experience level in Computer Science, Data Science, AI Engineer, ML Ops Engineer, or similar discipline.
- Extensive experience developing clean and efficient software in Python.
- Significant experience with data wrangling libraries such as pandas, numpy, and PySpark.
- Significant experience with machine learning and deep learning frameworks such as Sklearn, SciPy, XGBoost, or Pytorch.
- Extensive experience with the ML development lifecycle and MLOps solutions (MLFlow or similar) for model versioning, registry, and experiment tracking.
- Knowledge of CI/CD pipeline implementation and containerization (Docker).
- Experience with SQL and No-SQL databases.
- Demonstrated ability to learn continuously and work autonomously.
- Comfortable working in a rapidly changing environment with dynamic objectives and fast iteration with users.
- Ability to work effectively within teams with mixed technical expertise.
- Native or fluent in English.
Nice to Have:
- Experience developing computer vision solutions.
- Experience with open-source LLM frameworks or Cloud-based managed LLM solutions.
- Experience with embedded machine learning.
- Experience within the motorsport industry.
- Experience working with Cloud Solutions, specifically AWS.