Sr Data Scientist I (Actuarial Science)
About the role
Are you an actuarial professional who wants to build models that influence underwriting, risk segmentation, and decision-making across the insurance industry, without being confined to traditional rate-making roles?
Responsibilities
Developing predictive risk models and attributes used by insurers in underwriting, segmentation, and decisioning workflows
Applying actuarial principles and statistical modeling techniques to assess risk and improve model performance
Designing and implementing models that are integrated into carrier underwriting processes and downstream pricing frameworks
Translating complex analytical outputs into clear, defensible insights for business and product stakeholders
Partnering with Product and Vertical teams to solve insurance-specific problems related to risk evaluation and segmentation
Maintaining and analyzing large, complex datasets, including data storage, processing, and quality assurance
Applying best practices for data validation, testing, and model performance monitoring
Collaborating with team members to share knowledge, strengthen capabilities, and contribute to a strong analytical culture
Maintaining a strong understanding of team tools, technologies, and evolving industry trends
Communicating progress, insights, and outcomes clearly to stakeholders
Supporting team excellence by upholding high standards of quality, accountability, and execution
Requirements
Minimum undergraduate degree in relevant field and 4+ years of relevant work experience
Or a master’s degree in a relevant field and 2+ years of relevant work experience
Or a PhD in a relevant field
Strong actuarial foundation, including experience applying actuarial concepts to insurance risk, underwriting, or segmentation problems
Progress toward actuarial credentials (ASA or equivalent) strongly preferred
Strong expertise in Python
Coding skills in R, SQL, ECL are a plus
Experience developing or supporting risk segmentation models (e.g., GLMs) in an insurance context and in Department of Insurance filings
Experience translating actuarial models into production-ready analytical solutions
Strong foundation in statistical and mathematical modeling, including model assumptions, diagnostics, and interpretability
This includes linear and non-linear models along with ML techniques
Extensive programming skills in Python and/or R for statistical modeling and data analysis