Actuarial Data Scientist
$150,000–$160,000 year
RemoteUnited States
Job Summary
Develop price elasticity curves to forecast rating impacts on retention, conversion, and customer lifetime value while building GLM-based rating factors and advanced predictive models. Forecast policyholder retention and conversion based on pricing and operational changes, then write advanced SQL procedures to pull from line item level veterinary bill databases. Evaluate product proposals for pricing viability and enterprise risk, support rate filings and regulatory objections, and monitor rating plan performance through loss ratios and churn metrics. Collaborate with product, underwriting, and BI teams to communicate complex actuarial concepts and propose innovative coverage concepts.
Required Qualifications
- ACAS designation required (or ASA working in health insurance)
- At least 5 years of experience working in an actuarial or data science P&C and/or Health insurance role
- At least 2 years of experience in an actuarial ratemaking and/or pricing modeling role
- Advanced knowledge of SQL is required
- Strong knowledge of R and/or Python is required
- Intermediate knowledge of Excel is required
- Advanced knowledge of generalized linear models (GLMs) is required
- The ability to review and evaluate data for quality, completeness, and reasonability is required
Desired Qualifications
- Intermediate knowledge of elastic net GLMs, k-means clustering, and geospatial statistics is desirable
- Experience performing competitor filing research in SERFF is a plus
- Comfortable or willingness to learn how to work with AI assisted coding tools, such as, Claude, GitHub Copilot, or Gemini
- Excellent verbal, interpersonal and written communication skills; an excellent team player able to apply innovative ideas and critical thinking
- Able to anticipate needs, innovate and flourish in a high-volume, fast paced environment
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