Lead Biometric Data Scientist / Actuary
- Lead the technical work and maintenance of research and development projects and products catering to a diverse range of stakeholders across the organization.
- Ensure stakeholder needs are understood, expectations are communicated and managed, and the ultimate solutions deliver value.
- Stay abreast of, and leverage, modern data science methods and statistical modelling techniques, implementing them as needed to create actionable insights.
- Work with potential stakeholders across the business to help them understand available tools, models, and data, leading discussions and troubleshooting any arising issues.
- Translate business needs into sustainable solutions. For example, design, build, and maintain software/tooling/datasets related to monitoring, modelling, and forecasting mortality across markets and geographies where RGA operates.
- Work with diverse datasets, finding, collating, cleaning, and standardizing datasets from multiple sources and geographies to understand mortality drivers and improvements (cause of death, socioeconomic data, etc.).
- Influence the direction of the Biometric R&D team by actively contributing to operational planning, strategic planning, and new initiatives.
- Stay informed of research surrounding major mortality and morbidity trends and drivers across RGA's key geographies.
- Set realistic and achievable deadlines for projects. Ensure required tasks are completed accurately within those deadlines.
- Supervise, review, and provide feedback on, in a timely manner, the work - including data, assumptions, modelling, testing and documentation - of team members across Global R&D.
- Mentor, train, and develop junior Biometric Research team members. Actively seek opportunities to develop the wider Global R&D team.
- Strong undergraduate degree in a STEM subject
- 7+ years' experience in statistical modelling for insurance or related applications
- Postgraduate degree and/or FIA, FSA or equivalent accreditation (Actuarial job title only)
- Exposure to working in and/or with Actuarial research/pricing teams in the insurance industry
- Reinsurance industry experience
- Experience of demographic or biometric assumption setting / experience analysis
- Advanced ability to manipulate, visualize, and analyze large volumes of data using common data science packages (like pandas, seaborn, data tables, ggplot, etc.), tools, and platforms.
- Advanced ability to code in SQL, R and/or Python; advanced understanding of what makes "good" code, set coding standards for key pieces of work.
- Strong understanding of core (mortality) modelling techniques (GLMs, ARIMAs, smoothing methods).
- Some knowledge of the Life Insurance industry and key products (annuities and assurances)
- Ability to take ownership in projects and drive them to completion
- Ability to translate business needs and problems into viable/accepted solutions
- Advanced life insurance and/or reinsurance industry and product knowledge.
- Experience of serving dashboards and data models / insights to business teams
- Experience of building R packages
- Knowledge of real-world data, medical, and underwriting data
- Knowledge of actuarial processes and concepts, life insurance underwriting
- Experience of common mortality model structures like the Lee Carter and APC models
- Gain valuable knowledge from and experience with diverse, caring colleagues around the world.
- Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought.
- Join the bright and creative minds of RGA, and experience vast, endless career potential.
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