Manager, Actuarial Data Science

Hippo

Hybrid

Quick summary

Work type: Hybrid
Location: Dallas, TXAustin, TXMorristown, NJSan Jose, CA
Salary: $185,000–$245,000 / yr
Posted: 10 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $180k

This role $215k

$105k most similar roles pay here $260k

This role pays more than 95% of similar roles. Most pay $152,150–$207,350 — the shaded band above. At the midpoint, this role pays about $215k versus about $180k for comparable roles.

Based on 239 similar postings.

Employer

About Hippo

Hippo Insurance is a home insurance company that offers proactive home insurance products using smart home technology and data to help homeowners prevent claims before they happen. Industry: Insurance Technology & Homeowners Insurance

Hippo currently has 7 open roles on FindRole.

Most-posted roles

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At a glance

TL;DR · Manager, Actuarial Data Science

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Join Hippo as a Manager in Actuarial Data Science, leading an insurance modeling team focused on developing pricing, underwriting, and growth models for the Homeowners program. You will build advanced Python and SQL-based tooling to enhance efficiency and scalability across actuarial workflows while collaborating closely with Pricing, Underwriting, Claims, Product, and Data Engineering teams. Ideal candidates have 7+ years of data science or actuarial modeling experience in personal lines P&C insurance, along with strong people management skills and proficiency in Python, SQL, and Git. Experience in loss cost modeling and catastrophe risk is a plus, as you will design and implement robust models within Hippo’s Airflow-based pipeline to drive business impact.

Skills

Python SQL Git Airflow CI/CD

What you'll do

Lead the development and annual build of by-peril loss models.
Expand modeling capabilities for conversion, retention, and aggregation to inform pricing strategy.
Implement and scale insurance models within Python-based pipelines for robust testing and validation.
Develop reusable analytical tooling in Python and SQL to improve efficiency across actuarial teams.
Partner with cross-functional teams to translate complex modeling insights into clear business recommendations.

What we're looking for

7+ years of experience in data science, analytics, or actuarial modeling within personal lines P&C insurance
Bachelor’s degree in statistics, mathematics, data science, or another quantitative field
Advanced proficiency in Python and SQL with experience using Git
Strong experience in loss cost modeling and exposure to demand, underwriting, and claims modeling
3+ years of people management experience including coaching and performance development
Knowledge of actuarial principles related to insurance pricing

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