RGA is looking to solve today's challenges through innovation and collaboration by developing data-driven solutions in longevity product development and pricing. The Senior Data Scientist will focus on internal mortality assumption development for longevity markets by leveraging new and existing data sources through exploratory analysis, insights, model maintenance, and model R.
Requirements
- 6+ years of experience developing statistical models (Regression, Decision Trees, Time Series, etc.)
- Statistical programs/languages (R or Python)
- Spreadsheet skills (Excel/VBA) and database applications (SQL, Snowflake, Oracle,...)
- Advanced predictive modeling skills: Tree-based models, GLMs, GAMs, etc.; Cross-Validation, Residuals and model diagnostics; Basic Statistical concepts for feature engineering (e.g. percentiles, standardization, correlations, risk ratios / chi-square test, splines, and other non-linear transformations)
- Advanced exploratory data analysis skills - Plots and graphics (BI/ggplot)
- Ability to compile, analyze, refine, model and interpret very large data sets as well as the ability to incorporate expert judgment into statistical modeling techniques
- Transform data to enhance its predictive value (feature engineering)
Responsibilities
- Lead, design, create, and interpret end-to-end models with a typical focus on mortality within longevity markets.
- Support Pricing team with insights from large datasets and support efforts to adopt robust bespoke assumptions in quotes.
- Evaluate new external data sources and explore new applications of non-traditional data sources for RGA in its various regions.
- Participate in the development and enhancement of underlying processes and recommends improvements in data analysis /modeling best practice standards
- Offer risk management skills to any data processing or modeling exercise:
- Liaise with RGA's data scientists across the globe about more sophisticated data science applications
- Contribute to RGA's global analytics community, routinely sharing, maintaining consistency of approach
Other
- Communicate with a variety of stakeholders at various levels of seniority
- Understand business context& where material scope for error lies
- Adhere to professional standards, best practices, and ethical guidelines
- Understand the strengths and limitations of a modeling approach
- Have a strong understanding on tools / techniques their actuarial peers will not have had a formal education in such as:
