Develop, enhance, and maintain casualty catastrophe models and analytics for emerging and systemic liability risks
Conduct mathematical, statistical, and data‑driven analyses to support model design, validation, and testing.
Translate research prototypes into scalable, production‑ready model components
Build and improve model development pipelines using Python, SQL, Git, and AWS‑based tools.
Analyze and synthesize data from multiple sources to support model parameterization, sensitivity testing, and robustness evaluation.
Collaborate closely with product, software, and client‑facing teams to integrate model methodology into Verisk products.
Leverage Generative AI and agentic AI tools to accelerate modeling, prototyping, workflow automation, and insight generation.
Contribute to technical documentation and clearly communicate assumptions, methodology, limitations, and results.
Support client inquiries by explaining model behavior and outputs in a clear, practical, and accessible way.
Present analytical findings to both technical and non‑technical audiences.

Bachelor’s or Master’s degree in statistics, mathematics, data science, actuarial science, economics, engineering, computer science, or another quantitative/STEM field
At least 1 year of professional experience in data science, statistical modeling, risk modeling, or a related technical field
Strong programming skills in Python and SQL
Experience using Git‑based development workflows
Experience working with AWS‑based cloud analytics or data workflows
Demonstrated ability to take analytical or statistical models from proof‑of‑concept to implementation
Proven experience using AI‑powered tools to support modeling, prototyping, automation, and productivity improvements
Strong written and verbal communication skills, with the ability to explain technical ideas to non‑technical audiences

Data Scientist I

Key skills