Data Scientist - Time Series & Anomaly Detection

To join our Team of Data consultants based in Geneva area, we are looking for a

Data Scientist - Time Series & Anomaly Detection (m/w)

As AI specialist , you will contribute to the development of an advanced machine learning solution in the motorsport and automotive domain.

The project focuses on building a robust anomaly detection system, combining data engineering, machine learning and software engineering practices to transform complex data into actionable technical insights.

Your Mission

• Design and implement data pipelines from raw data to ML-ready datasets Develop and optimise machine learning models for time-series analysis and anomaly detection
• Build explainable AI solutions enabling users to understand model outputs
• Define performance indicators and analytical frameworks
• Establish MLOps foundations including experiment tracking, model lifecycle management and reproducible workflows
• Produce technical documentation and support knowledge transfer. You will collaborate with experienced engineering and data teams in a highly technical environment combining AI, software development and advanced analytics.

• You have minimum 6 years of experience in Machine Learning Engineering / Data Science ideally in motorsport, automotive, aerospace, environments
• Strong expertise in time-series data and anomaly detection
• Advanced Python skills and experience with ML frameworks
• Experience developing end-to-end machine learning solutions
• Knowledge of MLOps practices and software engineering standards
• Ability to translate complex technical outputs into clear insights
• Fluent French and English mandatory

Expleo offers a unique offer of integrated engineering, quality and strategic consulting services for digital transformation. In a context of technological acceleration, we are the trusted partner of companies that innovate. We help them develop a competitive advantage and improve the lives of millions of people. Joining Expleogroup means 17,000 employees in 30 countries, but also: * Have technical and human support for each project and effective follow-up of your career * Carry out training to develop professional skills * Participate in dedicated special events * Integrate a dynamic team