R&D Data Scientist — Autonomous Driving Data & Global Impact

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

Résumé du poste

Capgemini Engineering, the world leader in engineering services, is seeking an R&D Data Scientist. You will analyse vehicle telemetry, driving and unstructured data to build interpretable features and profiles, linking real-world data with survey responses to create rich driver insights.

You will review literature, test approaches with proofs-of-concept on messy data, and compare methods with focus on robustness. Strong Python, ML background, and fluent English are required.

Qualifications

• Proficient in Python for analysis, modelling and prototyping.
• Strong foundations in statistics, machine learning and AI.
• Ability to read and critically assess technical material and design experiments.
• Engineering sensibility to interpret data in real-world contexts.

Responsabilités

• Analyse vehicle telemetry, driving data and unstructured data to build interpretable features.
• Link telemetry with survey data to profile drivers.
• Review literature and test methods via proof-of-concepts on real data.
• Compare analytical methods with rigorous robustness and limitations.
• Collaborate with engineers and communicate results to diverse stakeholders.

Connaissances

Python for analysis

Statistics

Machine learning

Feature engineering

Dimensionality reduction

Model validation

Critical reading of technical material

Experiment design

Independent work

Communication

Fluent in English

Minimum 4 years experience

Outils

Pandas

NumPy

scikit-learn

Description du poste

Capgemini Engineering, the world leader in engineering services, is seeking an R&D Data Scientist. You will analyse vehicle telemetry, driving and unstructured data to build interpretable features and profiles, linking real-world data with survey responses to create rich driver insights.

You will review literature, test approaches with proofs-of-concept on messy data, and compare methods with focus on robustness. Strong Python, ML background, and fluent English are required.