Job Description

🧠 Role Overview

This position sits within RGA’s Biometric Assumptions Team, focusing on:

👉 Mortality modeling
👉 Longevity product development
👉 Insurance pricing analytics
👉 Predictive modeling for risk assumptions

It is a data science + actuarial + insurance domain hybrid role.

Unlike many tech company roles, this one emphasizes statistical rigor and business risk modeling rather than deep learning or AI products.

🚀 Key Responsibilities

1️⃣ Mortality & Longevity Modeling

You will:

• Build statistical models related to:
  • Mortality rates
  • Life expectancy
  • Longevity risk
• Develop internal assumptions used in insurance pricing

This directly impacts financial risk decisions.

2️⃣ Pricing & Business Insights Support

Work closely with:

• Actuaries
• Pricing teams
• Business developers

Your models help:

• Quote insurance deals
• Improve product pricing
• Reduce financial risk exposure

3️⃣ Data Exploration & Innovation

You’ll evaluate:

• External datasets
• Non-traditional data sources
• New modeling techniques

Focus is on practical impact, not academic experimentation.

4️⃣ Model Governance & Risk Awareness

Important part of this role:

• Understand model limitations
• Ensure quality assurance
• Follow ethical standards
• Identify risk exposure areas

Insurance companies treat models as regulated assets, so governance matters.

5️⃣ Global Collaboration

You’ll collaborate with:

• Data scientists worldwide
• Actuarial teams
• IT and business stakeholders

This is a highly cross-functional environment.

🎯 Core Skill Requirements

Technical Stack

Strong emphasis on classical statistics:

• Regression models
• Decision trees
• Time series
• GLM / GAM
• Feature engineering
• Cross-validation & diagnostics
• Exploratory data analysis

Programming:

• Python or R
• SQL
• Excel / VBA
• Databases (Snowflake, Oracle)

⭐ Preferred (High-Value) Skills

These can significantly increase your chances:

• Insurance or reinsurance experience
• Longevity / mortality analytics
• Actuarial knowledge
• Actuarial certifications (ASA/FSA, FIA)
• Experience studies / assumption modeling
• AXIS or Prophet platforms

This shows the role is close to actuarial science + data science.

🎓 Experience Level

Typical candidate:

• 6+ years modeling experience
• Bachelor’s minimum
• Master’s / PhD preferred
• Insurance domain helpful but not mandatory

💰 Compensation

• Salary: $123,500 – $184,050
• Bonus eligible
• Possible long-term equity incentives
• Full benefits package

Competitive for insurance analytics roles.

🌍 Location Flexibility

Options:

• Hybrid:
  • St. Louis
  • Toronto / Montreal
  • London
• Fully Remote possible

🔥 What Makes This Role Unique

Compared to tech company data science jobs:

✅ Strong statistical depth
✅ Direct business impact (pricing & risk)
✅ Collaboration with actuaries
✅ Stable industry (insurance)
✅ Less hype, more rigor

⚠️ Not Ideal If You Want

This may not be the best fit if your goal is:

• Pure AI / deep learning research
• Big tech product development
• Generative AI focus
• Startup environment

🆚 Comparison With Walmart Role You Shared Earlier

Feature	RGA Role	Walmart Role
Industry	Insurance	Retail / Marketing
Focus	Mortality modeling	Marketing AI & MMM
Math Depth	High statistics	High Bayesian + AI
Engineering	Moderate	Very high
Leadership	Moderate	High
Stress Level	Lower	Higher
Innovation	Moderate	Cutting edge
Stability	Very high	High

👍 Good Career Paths After This Role

• Principal Data Scientist (Insurance)
• Actuarial Analytics Lead
• Risk Modeling Director
• Chief Data Scientist (Insurance)
• Quantitative Risk Leader

✅ Who Is Perfect For This Job

Someone who enjoys:

• Statistics more than deep learning
• Business impact modeling
• Insurance / finance domain
• Structured environments
• Long-term stability