Quantitative Modelling Specialist (Life & Health)

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.

• 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.

• 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.