Head of L&H Data Foundation

Data is at the core of SCOR’s strategic plan Forward 2026 as one of its key enablers. The Chief Data Officer organization plays a central role in delivering a governed, trusted data platform acting as a Single Version of Truth across the organization. 

As Head of L&H Data Foundation, you are accountable for the end-to-end data foundation for the Life & Health domain, ensuring that data is correctly sourced, validated, transformed, and modeled into robust Analytical Data Models. 

Your primary responsibility is to ensure that data accurately reflects the business reality, from underwriting to claims and actuarial processes, and that this consistency is maintained across the full data lifecycle. This includes ensuring that data supports the consistent calculation and interpretation of key business metrics such as premiums, claims, reserves, and performance indicators. 

You lead agile, cross-functional squads, driving a product-based delivery approach focused on continuous value delivery. You act as the key interface between business, analytics, and engineering teams, ensuring that data solutions are both technically sound and business relevant. 

While contributing to governance and platform evolution, your core focus is to ensure that the foundations are built correctly to enable scalable analytics and AI use cases, with ADMs serving as the trusted representation of the business. 

• +7 years of proven experience as a Data Product Owner, Data Product Manager, or Data Foundation Lead in a data-driven environment 

• Strong experience in end-to-end data flows, including sourcing, transformation, and data modeling 

• Expertise in data modeling concepts and building Analytical Data Models or similar structures 

• Proven ability to ensure data quality and correctness across data pipelines, including upstream dependencies 

• Strong understanding of business processes and how data supports performance measurement and decision-making 

• Prior experience in Life & Health insurance or reinsurance, and familiarity with key KPIs and financial metrics (such as premiums, claims, reserves, or profitability indicators), is a strong advantage 

• Actuarial background or experience working closely with actuarial teams is a strong advantage, particularly in relation to modeling and interpreting business metrics and KPIs 

• Experience working with modern data platforms (e.g., Databricks, Palantir Foundry or similar) 

• Experience leading agile delivery in cross-functional teams 

• Strong communication and stakeholder management skills 

• Solid understanding of data governance principles and data management frameworks 

• Strong analytical and problem-solving skills, with a focus on root-cause analysis 

• Excellent organizational skills, systematic thinking, and objective-driven mindset 

• Strong dedication to quality and client orientation 

• Proficiency in English; French is a plus 

• Willingness to travel 

• Own the ADM and business ontology roadmap for the L&H domain, aligning with business priorities and the broader data strategy 

• Ensure that data is correctly sourced from upstream systems, with aligned definitions, structure, and ownership 

• Establish robust controls and validation mechanisms at ingestion and transformation stages to ensure data accuracy and completeness 

• Drive the design of Analytical Data Models that reflect L&H business processes (underwriting, claims, actuarial), not system structures 

• Ensure that ADMs provide a consistent and trusted representation of key business metrics and KPIs across the Life & Health domain 

• Ensure end-to-end consistency from source systems to ADM, including transformation logic, lineage, and reconciliation 

• Ensure data quality is managed across the full lifecycle, including root-cause analysis and remediation of upstream issues 

• Lead and coach cross-functional agile squads, driving a product-based delivery model with clear backlog prioritization and continuous value delivery 

• Act as the primary interface between business and data teams, ensuring strong validation, ownership, and alignment with business processes 

• Drive experimentation with AI and AI agents to improve efficiency in data sourcing, modeling, validation, and overall delivery processes