Senior Data Scientist – (Open to Remote)

Filled
February 23, 2026
Apply Now

Job Description

Company: Reinsurance Group of America (RGA)
Compensation: $123,500 – $184,050 USD + bonus + potential equity
Locations: Hybrid (St. Louis, Toronto, Montreal, London) or Fully Remote

About the Role

RGA is seeking a Senior Data Scientist to join its Biometric Assumptions Team, focusing on mortality modeling and longevity product development. This role blends advanced predictive analytics with actuarial collaboration to support pricing, risk assessment, and innovative insurance solutions across global markets.

The position offers strong exposure to actuarial science, insurance analytics, and large-scale predictive modeling in a highly specialized domain.

Key Responsibilities

Modeling & Analytics

  • Lead end-to-end development of predictive models focused on mortality and longevity risk.
  • Apply statistical and machine learning techniques to large datasets for pricing and assumption development.
  • Maintain, enhance, and research new modeling approaches.

Business Collaboration

  • Partner with pricing teams, actuaries, IT, and business leaders.
  • Translate analytical findings into actionable business insights.
  • Support adoption of robust assumptions in insurance quotes and product design.

Data Innovation

  • Evaluate new internal and external data sources.
  • Explore non-traditional data applications across global markets.
  • Improve modeling processes and analytics standards.

Risk & Governance

  • Ensure model transparency, quality assurance, and ethical standards.
  • Identify modeling limitations and risk exposure areas.
  • Contribute to global analytics best practices across RGA teams.

Required Qualifications

  • Bachelor’s degree in:
    • Mathematics
    • Statistics
    • Actuarial Science
    • Economics
    • Computer Science
    • Finance or related field
  • 6+ years of statistical modeling experience.
  • Strong programming skills in Python or R.
  • Database experience (SQL, Snowflake, Oracle).
  • Expertise in:
    • Regression, decision trees, time series
    • GLMs, GAMs, tree-based models
    • Feature engineering & model diagnostics
    • Exploratory data analysis & visualization

Preferred Qualifications

  • Insurance or reinsurance experience.
  • Longevity or mortality modeling background.
  • Master’s or PhD.
  • Actuarial designation (ASA/FSA or equivalent).
  • Experience with actuarial tools (AXIS, Prophet).
  • Knowledge of machine learning methods (SVMs, neural networks, clustering).
  • Basic data engineering skills.

Ideal Candidate Profile

This role is best suited for someone who:

  • Has 6–10+ years of data science or actuarial analytics experience.
  • Enjoys combining statistics with real-world financial risk modeling.
  • Can collaborate across technical and business stakeholders.
  • Wants exposure to global insurance markets and longevity research.

Why This Role Stands Out

✅ Remote flexibility with global collaboration
✅ High-impact work in life & health financial protection
✅ Strong compensation + bonus + equity potential
✅ Opportunity to work alongside actuaries and domain experts
✅ Exposure to cutting-edge longevity analytics and biometric modeling