Manager, Medical Analytics, R&D
On-siteLondon, England, United Kingdom
London, England, United KingdomOn-siteFull TimeLarge
Full TimeLarge
Job Summary
Conduct analytical projects to support UK individual and enhanced annuities basis development, including project and stakeholder management. Synthesize evidence, source data, design and validate models, and transform quantitative and qualitative insights into assumptions and uplifts for pricing, underwriting, and product development. Collaborate with Savings and Retirement, Protection, and global R&D teams to ensure analyses meet business needs while supporting thought leadership initiatives and knowledge sharing. Requires strong problem-solving, organizational, and stakeholder management skills.
Required Qualifications
- Qualified Fellow of the Institute or Faculty of Actuaries or other similar actuarial organisation
- advanced qualification in a health-related subject (e.g. Masters/PhD in Epidemiology, Biostatistics, Health Data Science or Health Economics)
- Strong analytical skills and independent problem-solving abilities applied in health-related contexts
- Excellent organisational skills and able to coordinate the work of multi-disciplinary teams in fast-paced commercial settings
- Proficient in turning quantitative and qualitative insights into practical and actionable outcomes
- Experience in explaining complex technical or commercial issues to a variety of audiences, via written and spoken communication
- Knowledge of modelling techniques such as survival models, disease progression models, simulation models, intervention models and causal inference
- An understanding of the reinsurance or insurance industry, particularly pricing, underwriting or assumption setting processes
- Experience of working with pricing and underwriting teams
- Knowledge of health data standards, health systems organisation or the pharmaceutical life cycle
- Ability to rapidly appraise medical research and synthesise evidence to inform analyses and commercial decision making
- Proficient in production-quality statistical programming, using languages such as R or Python
Desired Qualifications
- Experience in explaining complex technical or commercial issues to a variety of audiences, via written and spoken communication
- Knowledge of modelling techniques such as survival models, disease progression models, simulation models, intervention models and causal inference
- An understanding of the reinsurance or insurance industry, particularly pricing, underwriting or assumption setting processes
- Experience of working with pricing and underwriting teams is particularly advantageous
- Knowledge of health data standards, health systems organisation or the pharmaceutical life cycle
- Ability to rapidly appraise medical research and synthesise evidence to inform analyses and commercial decision making
- Proficient in production-quality statistical programming, using languages such as R or Python
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