Data is a core pillar of SCOR’s Forward 2026 strategic plan and beyond. Our ambition is to enable trusted, governed, and accessible data so that business teams can generate insights faster and make better decisions.
As a Data Analytics Engineer within the Chief Data Officer organization, you will design and deliver analytics ready datasets and curated data products that power dashboards, reporting, and analytical use cases within one primary business domain: Property & Casualty, Life & Health, or Finance.
A critical aspect of this role is a strong understanding of the business domain you are supporting. You are expected to develop deep knowledge of key processes, metrics, and decision drivers within your assigned domain, and to translate this business understanding into robust analytical data models, consistent KPIs, and meaningful datasets.
You will work at the intersection of data engineering and analytics, shaping data models, implementing transformations, ensuring data quality, and making datasets discoverable and usable for business consumers on SCOR’s enterprise data foundation (Genesis) and modern data platforms.
The Data Analytics Engineer is a professional who is: ·
• Outcome driven: Focuses on delivering datasets and metrics that materially improve business steering and decision making (timeliness, trust, usability).
• Data product minded: Treats analytical datasets as products with clear contracts (definitions, grain, lineage, quality expectations, documentation). ·
• Quality & governance oriented: Designs datasets that are consistent, auditable, and aligned with governance expectations (definitions, controls, traceability). ·
• Collaborative bridge-builder: Works effectively with business stakeholders, Data Foundation, Governance, Analytics & AI, and Platform teams to translate needs into robust analytical assets.
• Clear communicator: Can explain complex data concepts in a practical way and build trust with both technical and non-technical stakeholders.
• Design, build, and maintain analytics‑ready datasets that directly support reporting, dashboards, and decision‑making within your business domain (P&C, L&H, or Finance). ·
• Translate business concepts, processes, and decisions into clear analytical data models, dataset structures, and reusable metrics. ·
• Ensure data quality, traceability, and documentation for analytical datasets (definitions, grain, assumptions, lineage, known limitations). ·
• Partner closely with business stakeholders (e.g. actuarial, finance, underwriting, performance steering) to understand analytical needs and deliver data products with real business impact. ·
• Contribute to and apply data governance standards and best practices at the analytical layer, in collaboration with Data Foundation and Governance teams. ·
• Support adoption of analytical datasets by ensuring they are understandable, discoverable, and fit for self‑service consumption. ·
• Collaborate with Platform, Analytics & AI teams to ensure tooling, standards, and architecture effectively support analytics delivery.
Core skills:
• Proven experience delivering analytics‑ready datasets used for AI, dashboards, reporting, and decision‑making in a complex data environment. ·
• Strong business understanding in at least one domain: Property & Casualty, Life & Health, or Finance, with the ability to reason about domain KPIs, metrics, and processes. ·
• Hands‑on experience with SQL and data transformations; experience with Python / PySpark is a strong plus. ·
• Experience working on modern data platforms such as Palantir Foundry and/or Databricks (or equivalent analytics platforms). ·
• Solid understanding of analytical data modeling and metric consistency across multiple consumers. ·
• Strong stakeholder collaboration skills, with the ability to align business and technical teams on definitions, priorities, and delivery. ·
• Structured thinking, strong ownership mindset, and focus on sustainable, production‑grade analytics delivery. ·
• Proficiency in English; French is a plus.
Required Education
· Degree in technical or quantitative discipline (e.g. data, engineering, applied mathematics, statistics) or equivalent professional experience.
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As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying “The Art & Science of Risk,” SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.
Working at SCOR means engaging with some of the best minds in the industry – actuaries, data scientists, underwriters, risk modelers, engineers, and many others – as we work together to find solutions to pressing challenges facing societies.
As an international company, our common culture is defined by “The SCOR Way.” Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.
SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.
Skills Required
- Proven experience delivering analytics-ready datasets used for AI, dashboards, reporting, and decision-making in a complex data environment.
- Strong business understanding in at least one domain: Property & Casualty, Life & Health, or Finance.
- Hands-on experience with SQL and data transformations; experience with Python/PySpark is a strong plus.
- Experience working on modern data platforms such as Palantir Foundry and/or Databricks.
- Solid understanding of analytical data modeling and metric consistency across multiple consumers.
- Strong stakeholder collaboration skills.
- Structured thinking, strong ownership mindset, and focus on sustainable analytics delivery.
- Degree in technical or quantitative discipline or equivalent professional experience.
What We Do
SCOR, one of the world’s largest reinsurers, serves more than 5,000 clients worldwide, providing a diversified and innovative range of solutions to control and manage risk. SCOR delivers advanced financial solutions, analytics and services across all dimensions of risk in Life & Health, Property & Casualty, and Investments. Reinsurance lies at the intersection of technical expertise and scientific progress. Models, data, and pricing and reserving tools are essential, yet they are never sufficient on their own. Sound risk decisions require expert judgment, experience and perspective. This is what we call the Art and Science of Risk. Reinsurance is a knowledge industry, where expertise grows through accumulation, transmission and practice. Across the Group, 3,600 experts based in more than 35 offices worldwide contribute to this collective intelligence. Actuaries, underwriters, risk management specialists, and Tech & Data experts transform data into insight, explore extreme scenarios, define the boundaries of insurability and help anticipate emerging risks. Together, they strengthen the resilience of SCOR, our clients and the societies we serve. This expertise is built through shared experience,continuous questioning and collective reflection. Like artists, we belong to schools of thought, learning first to observe, then to replicate, and ultimately to innovate. This ongoing transmission of knowledge enables SCOR to develop a distinctive approach, combining rigor, creativity and long-term vision in the service of risk mastery. This shared commitment underpins SCOR’s role as a global reinsurer. By turning risk into resilience and sustainable value, our collective of experts acts with responsibility and purpose. Together, we help protect the future, and shape it, for our clients, for society and for generations to come.
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