Data Scientist
Models that hold up on real data, and results explained to the people who use them.
You frame business problems with client teams and translate them into concrete data and AI use cases with measurable outcomes. You build, evaluate and monitor machine learning models on real client data, combining classical ML with generative AI where it makes sense. And you explain clearly what they do, limits and risks included.
Your missions
Frame business problems with client teams and translate them into concrete data and AI use cases with measurable outcomes.
Build, evaluate and monitor machine learning models (fraud detection, scoring, recommendation, forecasting) on real client data.
Combine classical ML with generative AI where it makes sense, and benchmark approaches before recommending one.
Explain results clearly to non-technical stakeholders, including the limits and risks of each model, in line with our "Human Approved AI" principle and AI Act requirements.
Share knowledge internally and take part in our Campus training sessions when your expertise is relevant.
Human Approved AI: every model explained, its limits included.
Must-haves
What we offer
A concrete playground: strategic projects, demanding clients, direct impact.
A tight team that moves fast and gives you real autonomy.
A culture that mixes high standards, kindness and a genuine taste for fun.
Competitive compensation, flexibility, and above all a job that means something.
Apply right here
No job boards, no forty-field form. Three things: your CV, a link that represents you, a one-minute video. No cover letter, we don't care.