As part of the Group Data team and reporting to the Group Chief Data Officer, this role contributes directly to Europ Assistance’s data strategy by turning the Group’s shared data assets into actionable insights, advanced analytics, and AI‑driven data products designed for cross‑country reuse.

Working on top of the enterprise data platform, the role sits at the intersection of business domains and data delivery, collaborating closely with Data Business Partners, Data Engineers, and BI teams. The scope covers hands‑on data analysis, exploratory and diagnostic work, as well as designing, building, and scaling analytical and data science solutions – ranging from descriptive and diagnostic analytics to predictive models and applied AI use cases.

The role also involves supporting business users on the analytics platform, sitting alongside business or local teams to help them implement their own analytics, and championing responsible AI practices – while ensuring alignment with Group standards on data quality, governance, and reuse across countries, enabling trusted, industrialized, and value‑driven AI at scale.

Responsibilities:

Analysis & Insights

• Conduct exploratory, descriptive, and diagnostic analyses on Group data assets to answer business questions and uncover opportunities across domains (claims, operations, customer, distribution).

• Translate ambiguous business problems into structured analytical approaches and deliver clear, actionable findings to non‑technical stakeholders.

• Partner with BI teams to enrich reporting with deeper analytical perspectives beyond standard dashboards.

Data Products & Models

• Design, build, and maintain predictive models and applied AI use cases (e.g. claims management, operational forecasting, fraud detection).

• Own the end‑to‑end data product lifecycle: from data sourcing and feature engineering to model training, validation, deployment, and monitoring.

• Ensure cross‑country reusability by designing solutions that accommodate varying data maturity levels and local specificities.

Enablement & Support

• Support and enable business users on the analytics platform, sitting alongside domain teams to help them implement their own analytics solutions.

• Act as a bridge between the data platform and the business: help teams formulate their analytical needs, prototype solutions, and build autonomy over time.

• Setup and contribute to the analytics community of practice by sharing best practices, reusable notebooks, and documentation.

Responsible AI & Governance

• Champion responsible AI practices: embed fairness, transparency, explainability, and privacy‑by‑design into every analytical workflow.

• Ensure all solutions comply with GDPR, Group compliance requirements, and internal data governance standards.

• Collaborate with Data Governance and Compliance teams to define and enforce quality and ethical standards for AI/ML outputs.

Preferred Experience

• Master degree in Data+ Perfect command of English (in written & in spoken)

• Background in data analysis & analytics, with the ability to translate business problems into data‑driven approaches and measurable outcomes.

• Solid foundations in data science, ML or applied AI, including statistical methods and predictive or descriptive models used in real business contexts.

• Proven ability to work with enterprise data platforms and large datasets, using SQL and Python.

• Good understanding of end‑to‑end data product lifecycles, from data sourcing and transformation to analytics, visualization, or model consumption, with a focus on building reusable data products across countries.

• Familiarity with cloud analytics and AI ecosystems (e.g. AWS analytics services, Microsoft Fabric, Power BI, or equivalent platforms used as analytics layers).

• Experience within the Insurance industry, and more specifically in actuarial science, is a plus.

• Strong business orientation and sense of ownership, with a genuine commitment to delivering value for operations, customers, and partners: we care about impact.

• Ability to collaborate openly and constructively across domains and geographies, contributing to a trust‑based and inclusive data community: we care about people.

• Clear and structured communication skills, able to explain analytical results, AI outcomes, and trade‑offs to non‑technical audiences: make it simple, make it useful

• Autonomy and reliability in delivery, with the ability to prioritize effectively while respecting Group standards and collective ways of working

Recruitment Process

HR - Technical test / N+1

Additional Information

• Contract Type: Full-Time

• Location: Saint-Denis

• Education Level: Master's Degree

• Experience: > 3 years

• Possible partial remote