S
SCOR
Data Scientist
Quantitative Modelling Specialist (Life & Health)
On-siteSeniorData ScientistJust posted
Role summaryAI-generated
This role focuses on enhancing SCOR’s internal model methodology for life and health risks, requiring deep quantitative expertise and Python-based software engineering. The specialist will design, implement, and govern robust, scalable modeling solutions that integrate L&H risk dependencies within SCOR’s broader risk framework.
Skills required
About this role
The successful candidate will bring strong quantitative and programming capabilities, sound software-engineering judgement and either existing knowledge of L&H insurance risks or a demonstrated ability to quickly develop expertise in new and complex domains.
Responsibilities
- Methodology: Enhance and maintain SCOR’s Internal Model methodology with a focus on L&H risks and dependencies with other risks.
- Software engineering & implementation: Design, develop and maintain robust, reliable and computationally efficient Python implementations of Internal Model methodologies, helping shape the architecture of the L&H modelling framework and applying sound software-engineering principles to ensure code quality, maintainability, scalability and performance.
- Model changes & governance: Perform model change impact assessments, contribute to methodological enhancements, maintain technical documentation and support cross-functional model development initiatives.
- Results analysis & communication: Analyse, visualise and communicate model results to internal stakeholders, with a particular focus on the drivers of L&H capital requirements.
- Collaboration: Collaborate with colleagues across Risk Management, Finance, L&H Business Units and Data/AI in Paris, Dublin, Zurich and Cologne.
Qualifications
- Several years of relevant professional experience in risk modelling, actuarial modelling, quantitative modelling or a related quantitative discipline.
- Strong Python programming skills and experience developing and maintaining large object-oriented applications, with a good understanding of software architecture, code quality and maintainability.
- Ability to translate quantitative methodologies into robust, efficient and maintainable software solutions and to improve the performance and scalability of modelling applications.
- Knowledge of Solvency II, the Swiss Solvency Test, IFRS17 or L&H insurance risks is an advantage.
- Solid quantitative background in mathematics, statistics, actuarial science, engineering, computer science or a related discipline.
- Analytical mindset, proactive attitude and strong communication skills.
- Ability to work effectively in an international, multidisciplinary environment.
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