Data Modeler - Finance

SCOR; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

SCOR is seeking a Data Modeler for the Finance domain within its Tech, Data & AI organization. The role focuses on designing, managing, and governing Finance data models across systems to support reporting, closing, planning, and decision-making.

You will translate complex Finance requirements into scalable structures and ensure enterprise-aligned data foundations. The successful candidate will work with Data Engineers, Architects, and Finance stakeholders in a matrix, international environment

Qualifications

• Strong data modeling experience (conceptual, logical, physical).
• Solid understanding of Finance data and processes.
• Experience building analytical data models for reporting/analytics.
• Proficiency in SQL and/or PySpark; familiarity with modern data platforms.

Responsabilités

• Design, build, and maintain Finance data models within Data Foundation.
• Develop analytical data models enabling scalable reporting and self-service analytics.
• Contribute to enterprise Finance data model with consistent definitions.
• Collaborate with Data Engineers, Architects, and Finance stakeholders to reflect business semantics.
• Ensure data consistency, lineage, and proper granularity in datasets.
• Support metadata management, glossaries, and data lineage with data stewards.
• Apply data modeling standards to improve quality and maintainability.
• Translate Finance requirements into robust data structures for operational and analytical needs.

Connaissances

Data modeling

SQL

PySpark

Databricks

Palantir Foundry

Data governance

Metadata management

Communication

Collaboration

Formation

MSc or PhD in computer science / data science

Outils

Databricks

Palantir Foundry

Description du poste

At SCOR, we combine the Art and Science of risk to help build more resilient societies. Data is at the heart of our mission. Within our Tech, Data & AI organization, we are looking for a Data Modeler in Finance who is passionate about data modeling, ensures consistency of business representations at enterprise level, and contributes to the quality and governance of Finance data foundations.

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.

We are seeking a Data Modeler for the Finance domain to join our Tech, Data & AI team. The successful candidate combines strong data modeling expertise with a solid understanding of Finance processes in a reinsurance context. You bring the ability to translate complex financial requirements into structured, scalable, and business-aligned data models.
This position goes beyond pure technical modeling: it requires ownership of how Finance data is represented across systems, ensuring consistency, traceability, and alignment with enterprise standards to support reporting, closing, planning, and decision-making.

This role is focused on designing and managing Finance data models within our Data Foundation (Databricks & Palantir Foundry), including analytical data models and contributions to the enterprise Finance data model. The objective is to enable reliable reporting, efficient financial processes, and scalable analytics and AI use cases.

Key duties and responsibilities

Under the responsibility of the Finance Lead Data Engineer, your mission will be to:

• Design, build, and maintain conceptual, logical, and physical data models for Finance within the Data Foundation (Databricks & Palantir Foundry), supporting financial processes such as closing, planning, and performance analysis
• Develop and evolve analytical data models that enable scalable reporting, self-service analytics, and AI-driven use cases.
• Contribute to the enterprise Finance data model, ensuring consistent business definitions and alignment across domains and systems
• Collaborate with Data Engineers, Architects, and Finance stakeholders to ensure models reflect business semantics and integrate into the overall data architecture.
• Ensure data consistency, reconciliation capability, and proper handling of granularity, time dimensions, and historical tracking in financial datasets.
• Support metadata management, business glossaries, and data lineage in collaboration with data stewards to provide transparent and governed Finance data.
• Apply and promote data modeling standards and best practices to improve quality, reusability, and maintainability of Finance data assets.
• Translate complex Finance requirements into robust and scalable data structures that support both operational and analytical needs.

Required experience & competencies

• Strong experience in data modeling, including conceptual, logical, and physical models.
• Proven experience in financial services, with a solid understanding of Finance data and processes.
• Experience building analytical data models for reporting and analytics.
• Proficiency in SQL and/or PySpark, with understanding of modern data platform architectures.
• Experience with Databricks and/or Palantir Foundry.
• Understanding of data governance, metadata management, and data quality principles.
• Strong analytical thinking, attention to detail, and ability to structure complex topics.
• Ability to collaborate effectively with both technical and business stakeholders.
• Excellent communication skills and ability to operate in an international, matrix environment

Required education

• MSc or PhD in computer or data science, software or computer engineering, applied math, physics, statistics, or a related field or equivalent experience.