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September 18, 2026

Senior Data Scientist

Senior • On-site

Quick Facts

  • Role: Senior Data Scientist

Description

Design, develop, and deploy advanced analytics and machine learning solutions that generate measurable impact on business activities.

Responsibilities

  • Design, develop, and deploy data science and machine learning models (segmentation, churn, fraud, marketing, forecasting, optimization)

  • Translate business problems into concrete, measurable analytics solutions

  • Lead end-to-end use cases: data exploration, feature engineering, modeling, evaluation, production deployment, and monitoring

  • Define performance metrics; ensure model robustness and manage evolution over time (recalibration, drift)

  • Collaborate closely with Data Engineering, IT, AI, and business teams to industrialize models

  • Document work and support business teams in adopting solutions

  • Ensure explainability, compliance, and responsible model use in regulated environments

  • Contribute to data science best practices and the development of reusable components and models

  • Act as a technical reference and help upskill more junior profiles

Requirements

  • 5 to 8 years of experience in applied data science, machine learning, or advanced analytics

  • Strong command of Python and SQL, and core machine learning techniques

  • Proven experience deploying models in production and collaborating with Data Engineering / IT teams

  • Good understanding of data quality, model performance, and monitoring

  • Ability to work on complex business problems and deliver pragmatic, actionable solutions

  • Excellent communication and collaboration skills with both business and technical stakeholders

  • Experience in insurance, finance, or a regulated environment (plus)

  • Master’s degree in Data Science, AI, Computer Science, or equivalent experience

  • Languages: fluent French (required); professional English (plus)

Benefits

Drive measurable business impact through end-to-end machine learning while ensuring model explainability, compliance, and responsible use in a regulated environment.

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