Reinsurance Group of America, Incorporated
Trusted Partner. Proven Results.
Senior Data Scientist – Longevity, Biometric Assumptions
Location
California + 4 moreAll locations: California, Connecticut, New York, Ohio, Massachusetts
Posted
21 days ago
Salary
$123.5K - $184.1K / year
Bachelor Degree6 yrs expEnglishOraclePythonSQLVBA
Job Description
• 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
• Communicate with a variety of stakeholders at various levels of seniority
• Offer risk management skills to any data processing or modeling exercise: 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: Understand applications, risks, transparency, quality assurance & peer review, and ethical guidelines
• Stay abreast of new techniques, but focusing on practical applications
• 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
Job Requirements
- Bachelor's degree in Math, Finance, Economics, Statistics, Actuarial Science, Computer Science or related field
- 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)
- Advanced ability to translate business needs and problems into viable/accepted solutions
- Advanced investigative, analytical, and problem-solving skills.
Benefits
- Health insurance
- Retirement plans
- Annual bonus plan
- Long-term equity incentive plan