Data Scientist

g2 Recruitment; Brussel Hoofdstad; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

g2 Recruitment is seeking a data scientist to support a vehicle behaviour and customer intelligence project. You will analyse vehicle and driving data, including unstructured verbatim data, to create interpretable features and driving pattern indicators.

You will link telemetry with surveys and personas, review relevant methods, run quick PoCs, compare modelling approaches, and collaborate with engineers to translate findings into actionable recommendations.

Qualifications

• Strong Python for analysis, modelling and prototyping.
• Solid AI, statistics and machine learning, including feature engineering, dimensionality reduction and model validation.
• Applied-research capability: read technical material, adapt methods, and design experiments on messy real-world data.
• Engineering sensitivity: understands what the data represents and whether results make physical/behavioural sense.
• Clear communication of assumptions, limitations and conclusions.

Responsabilités

• Analyse vehicle data, driving data, and unstructured data to build interpretable features and dimensions.
• Link telemetry data with surveys, personas and behavioural indicators.
• Review relevant methods or papers and test them quickly through PoCs on real data.
• Compare approaches (clustering, dimensionality reduction, factor analysis, correlation) and validate robustness.
• Work with engineers to ensure results are technically meaningful and communicate findings with clear recommendations.

Connaissances

Python for analysis

AI & ML fundamentals

Applied research

Engineering sensitivity

Clear communication of assumptions

Outils

SQL

Snowflake

Databricks

LLMs / AI-assisted analytics

Description du poste

Duration - October-April (likely extension)

Context

Support an ongoing vehicle behaviour and customer intelligence project (R&D environment), linking real-world vehicle telemetry with survey data. The work is applied: applying and adapting data science, statistical and AI methods to complex engineering data, and turning ideas into practical, explainable results.

What the person will do

• Analyse vehicle data, driving data, unstructured data (e.g. verbatim) to build interpretable features and dimensions to define driving patterns and behaviours.
• Link telemetry data with surveys, personas and behavioural indicators.
• Review relevant methods or papers, judge what is applicable, and test it quickly through PoCs on real data.
• Compare approaches (clustering, dimensionality reduction, factor analysis, correlation analysis, supervised/unsupervised modelling) and validate them properly (robustness, reliability, limitations).
• Work with engineers to ensure results are technically meaningful, and communicate findings with clear recommendations.

Must have

• Strong Python for analysis, modelling and prototyping.
• Solid AI, statistics and machine learning, including feature engineering, dimensionality reduction and model validation.
• Applied-research capability: able to read technical material, adapt methods, and design experiments on messy real-world data - not only run standard pipelines.
• Engineering sensitivity: understands what the data represents and whether results make physical/behavioural sense.
• Clear communication of assumptions, limitations and conclusions.

Nice to have

• Survey / customer behaviour / persona / UX analytics experience.
• SQL, Snowflake, Databricks or similar platforms.
• Applied use of LLMs or AI-assisted analytics.