Senior Data Scientist

Role overview Own the development and production deployment of pricing and risk models for homeowners insurance. The work centers on generalized linear models while also covering machine learning, profitability and retention analysis, and geospatial risk. You will collaborate with actuarial, product, and engineering partners to turn property data into models that support underwriting and pricing decisions.

Responsibilities - Build, validate, and deploy models for claim frequency, severity, and loss cost. - Develop machine learning models to improve underwriting accuracy and pricing competitiveness. - Contribute to profitability, retention, and geospatial risk modeling. - Evaluate emerging methods, including generative AI, for potential use in insurance modeling. - Help establish consistent standards and practices for pricing and risk models. - Mentor junior data scientists through code reviews, knowledge sharing, and technical guidance.

Requirements - Experience taking complex data science or insurance modeling problems from initial scoping through production deployment. - Strong practical expertise in generalized linear models for insurance pricing. - Ability to build and assess machine learning models, including gradient-boosted models or neural networks. - Skill in communicating and working across actuarial, product, and engineering teams.

Benefits and work setup - Remote position based in the United States.