Actuarial Data Scientist: Homeowners Modeling & Pricing

Hippo Insurance; San Jose (CA); Hybrid; USD 145,000 - 180,000; Full time

Benefits offered by this job

Relocation Assistance

Healthy Hippos Benefits

Equity

Training and Career Growth

Flexible Time Off

Little Hippos Program

Hippo Habitat

Job summary

Hippo is hiring an Actuarial Data Scientist to lead loss cost modeling for its Homeowners program, owning design, development, and deployment of predictive models for frequency and severity.

You will build and scale Python-and-SQL tooling embedding expected loss ratio and segmentation analytics into production workflows, with opportunities to expand modeling across demand and pricing decisions.

Qualifications

• Bachelor’s degree in statistics, mathematics, data science, or another quantitative field.
• 5+ years of experience in data science, analytics, or actuarial modeling in insurance.
• 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.

Responsibilities

• 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

Skills

Data science

Actuarial modeling

Python

SQL

GLMs

XGBoost

LightGBM

Model validation

Actuarial pricing

Communication

Airflow

AWS

Education

Bachelor’s degree in statistics / math / data science

Master’s degree preferred

Tools

Airflow

AWS

Job description

Hippo is hiring an Actuarial Data Scientist to lead loss cost modeling for its Homeowners program, owning design, development, and deployment of predictive models for frequency and severity.

You will build and scale Python-and-SQL tooling embedding expected loss ratio and segmentation analytics into production workflows, with opportunities to expand modeling across demand and pricing decisions.