Reinsurance Group of America, Incorporated

Trusted Partner. Proven Results.

Senior Data Scientist – Longevity, Biometric Assumptions

Full TimeRemoteTeam 1,001-5,000Since 1973H1B No SponsorCompany SiteLinkedIn

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

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