Actuarial Data Scientist — Loss Modeling Lead (Relocation)

Hippo; Austin, Dallas, Morristown, San Jose (TX, TX, NJ, CA); On-site; USD 145,000 - 160,000; Full time

Benefits offered by this job

Relocation Assistance

Healthy Hippos Benefits

Equity

Training and Career Growth

Flexible Time Off

12 weeks Parental Leave

Hippo Habitat

Job summary

Hippo is hiring an Actuarial Data Scientist to lead loss cost modeling for the Homeowners program. You will design, develop, and deploy predictive models for frequency and severity, aligning with pricing strategy and business goals.

Build and scale Python- and SQL-based tooling into production-ready workflows, embedding loss ratio analysis. You’ll expand modeling capabilities across demand, aggregation, and pricing, partnering with cross-functional teams to translate insights into actionable

Qualifications

• Bachelor’s degree in statistics, mathematics, data science, or quantitative field; advanced degree a plus
• 5+ years in data science, analytics, or actuarial modeling in insurance
• Knowledge of P&C insurance in loss cost modeling
• Strong background in statistical modeling: GLMs, regularization, tree ensembles (XGBoost, LightGBM)
• Knowledge of actuarial pricing principles
• Proficiency in Python (pandas, scikit-learn, statsmodels) and SQL
• Excellent communication and stakeholder management

Responsibilities

• Lead homeowners insurance modeling with clear priorities and standards
• Own design and annual build of by-peril loss models
• Expand modeling capabilities across conversion, retention, and aggregation
• Implement and scale models in Airflow-based Python pipeline with robust testing
• Develop reusable analytical tooling and workflows for the actuarial team
• Collaborate with Product, Underwriting, and Engineering to translate insights into decisions

Skills

Python

SQL

GLMs

XGBoost

LightGBM

Communication

Education

Bachelor's degree in Statistics/Math/Data Science

Tools

Airflow

Pandas

scikit-learn

Statsmodels

Job description

Hippo is hiring an Actuarial Data Scientist to lead loss cost modeling for the Homeowners program. You will design, develop, and deploy predictive models for frequency and severity, aligning with pricing strategy and business goals.

Build and scale Python- and SQL-based tooling into production-ready workflows, embedding loss ratio analysis. You’ll expand modeling capabilities across demand, aggregation, and pricing, partnering with cross-functional teams to translate insights into actionable