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# Actuarial Data Scientist

- **Company:** Hippo Holdings Inc.
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $145,000 - $160,000
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Cloud Computing, Data Infrastructure, Python (Programming Language), Standard Sql, Software Deployment, SQL Databases, Workflow Management Systems, Model Validation, Pandas, Scikit Learn, Statistics Packages, Xgboost
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/actuarial-data-scientist-san-jose-ca--a97d3303-9ad5-46eb-bdc4-2e1cbd4209c3

## About the Role

Actuarial Skills, Data Science, Actuarial Skills, Data Science, Logistics, Continuous Improvement, Customer Experience, Predictive Modeling, Machine Tool, Pricing, * Bachelor's degree in statistics, mathematics, data science, or another quantitative field; advanced degree a plus

 * 5+ years of experience in data science, analytics, or actuarial modeling in insurance, preferably personal lines or property
 * Working knowledge of P&C insurance in loss cost modeling; exposure to demand, underwriting, and/or claims modeling
 * Strong background in statistical modeling: GLMs, regularization, tree-based ensembles (XGBoost, LightGBM), and model validation techniques
 * Knowledge of actuarial principles as they relate to insurance pricing
 * Advanced proficiency in Python (pandas, scikit-learn, statsmodels) and SQL
 * Excellent communication skills and ability to build trust with stakeholders at all levels

Nice to Haves:

 * Actuarial credentials - ACAS/FCAS
 * Master's degree in a quantitative discipline
 * Experience working in modern data platforms, including familiarity with cloud infrastructure (e.g., AWS) and workflow orchestration tools (e.g., Airflow)
 * Experience with catastrophe modeling, geospatial analytics, or climate risk data

The base pay range for this role is $145,000- $160,000 for our Texas (Austin and Dallas regions). The SF Bay Area (and New Jersey) base pay range for this role is $155,000- $180,000. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, location, business needs and market demands.

## Description

We're hiring an Actuarial Data Scientist to lead loss cost modeling for Hippo''s Homeowners program. This role will own the design, development, and deployment of predictive models for frequency and severity, ensuring strong alignment with pricing strategy and business objectives. You''ll build and scale Python-and SQL-based tooling that embeds expected loss ratio and segmentation analytics into reusable, production-ready workflows. In addition to leading loss cost modeling, you''ll have the opportunity to expand the team''s modeling capabilities across the demand and aggregation models to inform broader pricing and business mix decisions.

About You:

You are a hands-on leader with a strong background in loss modeling. You bring structure to ambiguity, enjoy building scalable work, and take pride in developing people on your team. You think critically about model maintenance cost and you balance scientific rigor with practical business impact. You communicate clearly, document thoroughly, and operate with a strong sense of ownership.

What You'll Do:

 * Lead homeowners insurance modeling efforts, setting clear priorities, technical standards, and best practices while fostering a culture of ownership, rigor, and continuous improvement
 * Own the design and annual build of our by-peril loss models
 * Expand modeling capabilities across conversion, retention, and aggregation to inform pricing strategy, business mix, and portfolio performance
 * Implement and scale models within our Airflow-based Python modeling pipeline, ensuring robust testing, validation, reproducibility, and long-term maintainability
 * Develop reusable analytical tooling and workflows that improve efficiency, consistency, and scalability across the actuarial team
 * Partner cross-functionally with Insurance Product, Underwriting, and Engineering to translate complex modeling insights into clear business recommendations and ensure successful production deployment