Head of Data Platform

At SCOR, we combine the Art and Science of risk to help build more resilient societies. Data and AI are at the heart of this ambition.

Within our Tech, Data & AI organization, we are seeking a Head of Data Platforms to lead the design, operation, and continuous evolution of SCOR’s enterprise data platform ecosystem, centered around Databricks and Palantir Foundry.

This role is for a senior leader who combines deep platform expertise, strong engineering leadership, and forward-looking innovation, especially in the agentic AI space. You will own the platforms that enable data, analytics, and AI at scale, ensuring they are trusted, governed, cost-efficient, and continuously scaling business growth and AI adoption.

You will play a critical role in shaping how SCOR leverages modern data platforms such as Databricks and Palantir Foundry (incl. AIP) to deliver high-impact business outcomes across underwriting, pricing, reserving, and corporate functions.

You will define and own the platform strategy, governance model, operating model, and engineering standards, ensuring that the platform enables scalable data products, AI use cases, and self-service analytics.

Beyond platform stability and delivery, you will drive innovation in the agentic AI space, enabling new ways of working through AI-powered workflows, automation, and decision intelligence. This role requires a strong balance between strategy, architecture, governance, and hands‑on leadership, with a particular focus on:

• Architecture, governance, and compliance (data, AI, access, regulatory)
• Cost management (Fin Ops for data and AI platforms)
• Platform standards, adoption and best practices
• Enabling business-driven use cases at scale

Key duties and responsibilities

Under the responsibility of the Head of Data Platform
, your mission will be to:

• Define and execute the enterprise data platform vision, architecture, and roadmap across Databricks and Palantir Foundry, aligned with SCOR’s business and AI strategy
• Own the end‑to‑end platform architecture, including ingestion, transformation, storage, analytics, and AI enablement layers
• Ensure the data platform scales in line with business growth, increased data volumes, and expanding AI use cases, while maintaining performance, resilience, and cost efficiency
• Lead the modernization and consolidation of legacy data systems into a unified, scalable platform ecosystem

2. Platform Enablement & Adoption

• Build and lead a Data Platform Center of Excellence (CoE) to drive adoption, onboarding, and enablement
• Support business to empower self‑service analytics and AI
• Act as a strategic partner to business and domain teams to prioritize, industrialize, and scale high‑value use cases in line with platform capacity and business demand

3. Governance, Security & Compliance

• Establish and enforce enterprise‑wide governance frameworks covering access control, and regulatory compliance
• Define and operate platform governance models
• Ensure alignment with regulatory requirements (e.g. data privacy, auditability, AI governance)

4. Cost Management & Fin Ops

• Own platform cost management (Fin Ops) across data and AI workloads, ensuring transparency, accountability, and optimization
• Implement cost control mechanisms
• Drive a culture where cost efficiency is embedded into engineering and data usage practices

5. Excellence & Best Practices

• Lead the definition of reference architectures, reusable patterns, and canonical datasets / data products
• Establish platform observability, monitoring, and operational excellence practices

6. Leadership & Stakeholder Management

• Lead and grow a high‑performing global team (platform engineers, architects, governance, Fin Ops)
• Collaborate with executive stakeholders to align platform investments with…