R&D Data Scientist — Automotive Telemetry & ML

Capgemini; Diegem; Sur place; EUR 60 000 - 90 000; Plein temps

Avantages offerts par ce poste

Empowering environment

FlexAbroad opportunities

Learning platform access

Global leader in engineering services

Résumé du poste

Capgemini Engineering is seeking an R&D Data Scientist to advance telemetry analysis, unstructured data and driver profiling. You will develop interpretable features, link real-world data with survey responses, and conduct rigorous experiments to drive actionable insights.

The role requires strong Python, statistics, and ML skills, independent work style, and the ability to explain complex results to diverse stakeholders.

Qualifications

• Strong proficiency in Python for analysis, modelling and prototyping.
• Solid foundations in statistics, machine learning and AI.
• Applied research capability and ability to design experiments on complex datasets.
• Engineering sensitivity to ensure results are meaningful and robust.

Responsabilités

• Analyze vehicle telemetry, driving data and unstructured data to build interpretable features and dimensions.
• Link real-world telemetry data with survey responses and driver personas to understand driver profiles.
• Review academic and technical literature and rapidly test approaches via proofs-of-concept on real data.
• Compare and validate analytical methods (clustering, dimensionality reduction, factor analysis, supervised/unsupervised modelling).
• Collaborate with engineers and clearly communicate recommendations to technical and non-technical stakeholders.

Connaissances

Python

Statistics

Machine learning

Data analysis

Communication

Autonomy

Outils

Pandas

Scikit-learn

Description du poste

Capgemini Engineering is seeking an R&D Data Scientist to advance telemetry analysis, unstructured data and driver profiling. You will develop interpretable features, link real-world data with survey responses, and conduct rigorous experiments to drive actionable insights.

The role requires strong Python, statistics, and ML skills, independent work style, and the ability to explain complex results to diverse stakeholders.