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Salary: USD 145,000 - 180,000 / annual
Hippo is a tech-native insurance platform that uses data and technology to help customers protect what matters most. The company operates as a diversified carrier platform, partnering with MGAs to deliver tailored program solutions.
You will lead loss cost modeling for Hippo's Homeowners program, owning the design, development, and deployment of predictive models for frequency and severity. Your work will ensure 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. Beyond loss cost modeling, you'll have the opportunity to expand the team's modeling capabilities across demand and aggregation models to inform broader pricing and business mix decisions.
Key responsibilities include:
- 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 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 the 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
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 balance scientific rigor with practical business impact. You communicate clearly, document thoroughly, and operate with a strong sense of ownership.
REQUIREMENTS:
- 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
