Actuarial Analyst

Overview

In this role, you contribute to an analytics-driven agenda within SCOR, supporting data projects that span analytics, programming, machine learning and R&D. You will lead and collaborate on high-profile initiatives across the global analytics team and with clients, helping improve risk pricing, data quality and customer outcomes. The position offers exposure to underwriting data, large datasets and innovative techniques, with opportunities to advance to senior leadership within projects that shape SCOR’s data-driven strategy.

Responsibilities

• Analyse and clean large data sets to build and validate predictive models
• Develop and improve risk pricing, data capabilities and MI for profitability and client management
• Collaborate with cross-functional stakeholders and clients to communicate results and insights
• Contribute to SCOR’s R&D activities, including mortality and morbidity trend analyses and base tables
• Identify and integrate new data sources to deliver value to clients and internal decision making
• Support the development of large internal databases aligned with the firm’s data strategy
• Generate documentation and presentations to share findings internally and externally
• Lead and participate in high-profile analytics projects within the team
• Address model validation, explainability and stakeholder communication

Key requirements

• Experience handling and analysing large datasets and data visualization
• Proficiency with Microsoft Excel/Access
• Coding knowledge in Python and/or R or a willingness to learn
• Desirable: knowledge of data science, machine learning, pricing experience with PROPHET and SAS
• Actuarial training welcome (trainees or those who have paused exams)

• Excellent analytical skills
• Self-motivation
• Customer focus
• Python
• R
• Data visualization

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