Data Scientist - F/H - Lille

MP Data • French: C1 • Python • SQL • 5 days ago
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Salary
$45k – $73k per year
Location
Hybrid (Lille, France)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Sep 17, 2026.

Overview
Company
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Profile match

MP Data

MP Data is a French data and AI consultancy that puts data at the heart of industry, offering data engineering, cloud data, machine learning and MLOps services. It hires data engineers, AI engineers, data scientists, lead architects and business managers in Boulogne-Billancourt, Lille and Balma. The company is headquartered in Boulogne-Billancourt, France.
mpdata.fr • HQ: Boulogne-Billancourt, France • Data Engineering & Migration Services • Industrial AI • Power Grid • 51-200 employees • Est. 2015
Tech stack of MP Data

Rejoignez MPdata, une entreprise spécialisée dans l'acquisition, le traitement et la valorisation des données pour les clients industriels. En tant que Data Scientist, vous serez responsable de concevoir, développer et déployer des solutions d'analyse de données avancées. Vous travaillerez en étroite collaboration avec les Data Engineers, DevOps et Product Owners pour garantir la cohérence de bout en bout.

Missions

  • Analyser, structurer et valoriser des jeux de données internes et externes.
  • Développer des modèles de machine learning (prédiction, scoring, segmentation, NLP, LLM, RAG, Computer vision, etc.).
  • Concevoir des pipelines de traitement de données robustes et automatisés.

Profil recherché

Ingénieur d’une grande école (Centrale, Mines, Supaero, Supelec, …), vous avez des connaissances en modélisation et machine learning (deep learning, random forest, svm…) acquises lors de vos expériences passées. Vous avez de bonnes connaissances en Python (ou R) pour coder ces algorithmes.

Vous êtes reconnu(e) pour votre autonomie, votre excellent relationnel et votre capacité à être force de proposition.

* Solide maîtrise de **Python** et des librairies ML (Scikit-learn, XGBoost, TensorFlow ou PyTorch).

* Expérience en **mise en production** de modèles ML (APIs, CI/CD, containerisation).

* Bonne connaissance des bases de données (SQL, NoSQL) et des outils de data pipeline (Airflow, Spark, etc.).

* Compétences en MLOps : versioning de modèles, monitoring, déploiement cloud (AWS, GCP, ou Azure).

* Aisance dans l’analyse métier et la vulgarisation des résultats.

* Goût pour l’optimisation, la performance et la qualité logicielle

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