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Data Scientist

Chicago, Illinois, United States; Fairfield, California, United States; Houston, Texas, United States💼 Full-time🗓 2026-08-11 → 2026-09-26

Core

Develop scalable analytical tools and models using geospatial analytics, statistical modeling, and machine learning to solve complex underwriting and risk management challenges in property insurance.

Role type

Data Scientist (Geospatial & Risk Modeling)

Builds

Scalable analytical tools, predictive models, and automated workflows for underwriting and risk management.

Domain

Insurance / Catastrophe Risk / Geospatial Analytics

Deliverable

production ML models | product features | dashboards & analysis

Required skills

Geospatial analytics, statistical modeling, machine learning, software development, predictive analytics, data pipeline construction, API development, data cleansing and transformation, causal inference, time series analysis, clustering, classification, regression.

Preferred skills

Experience with large and complex datasets, modern AI techniques, mentoring junior team members.

Technologies

(Not explicitly listed)

Responsibilities

Design and develop statistical, geospatial, and machine learning models to improve underwriting performance; analyze spatial, exposure, catastrophe, and loss data to identify trends and risk concentrations; execute predictive analytics and AI models to support pricing and operational efficiency; build reusable data pipelines and automate data collection and transformation; design and maintain geospatial datasets using internal and third-party sources; develop software applications and APIs to support underwriting analytics; mentor junior team members on AI best practices.

Seniority

Mid-Senior, hands-on IC

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