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Job Description
Operations Research Scientist / Senior Operations Research Scientist - London (Hybrid working)
Job Description
Chubb is a world leader in insurance. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, underwriting excellence, superior claims handling expertise and local operations globally.
Key Objectives
The Global Analytics- Operations Research team at Chubb is looking for a Operations Research Scientist/ Sr. Operations Research Scientist to join our fast-paced, high-energy team responsible for delivering cutting edge solutions leveraging operations research techniques. This position offers the opportunity to lead innovative projects and advance Chubb’s AI-driven Solutions.
Key Responsibilities
- Design and implement optimization solutions for use in insurance risk profiling, claims management and other key opportunity areas.
- Lead simulations and analysis of business strategies to validate robustness and inform decision-making.
- Partner with cross-functional teams including actuaries and underwriters to translate business requirements into mathematical frameworks, ensuring practical and scalable implementation of optimization models.
- Build and maintain production-ready optimization engines that scale across different insurance products and use cases, working with IT to ensure performance and reliability of deployed solutions.
- Drive continuous improvement by applying new techniques, mentoring team members, and leading initiatives to enhance decision-making capabilities.
Qualifications
Qualifications:
- Advanced degree (Master’s or Ph.D.) in Industrial Engineering, Operations Research, Applied Mathematics, or related fields.
- Deep expertise in optimization modelling, algorithm design, and simulation techniques with proven experience implementing practical solutions.
- Demonstrated ability to translate mathematical concepts into business insights and recommendations for non-technical stakeholders.
- Proficiency in Python and experience with optimization tools like Gurobi, CPLEX or similar.
- Must be able to do work Hybrid at least 3 days in the office and you can work 2 days from home.
