<p>At Verisk, we help the world see new possibilities and inspire change for better tomorrows. Within our Catastrophe & Risk Solutions business, we are the scientific leader in catastrophe modeling-pioneering the industry since 1987 and modeling risk from natural catastrophes, terrorism, and casualty threats across 90 countries.</p> <p>We are seeking a Data Scientist I to join our Casualty Catastrophe Model team in Boston. This is an exciting opportunity to work at the intersection of data science, probabilistic modeling, insurance analytics, and software-enabled product development, helping global clients better understand and manage emerging and systemic liability risks.</p> <p>What You'll Do</p> <p>As a member of our research and modeling organization, you'll contribute across the full model development lifecycle-moving ideas from research and proof-of-concept through to production-ready solutions used by clients around the world.</p> <p>In this role, you will:</p> <ul> <li>Develop, enhance, and maintain casualty catastrophe models and analytics for emerging and systemic liability risks </li><li>Conduct mathematical, statistical, and data-driven analyses to support model design, validation, and testing. </li><li>Translate research prototypes into scalable, production-ready model components </li><li>Build and improve model development pipelines using Python, SQL, Git, and AWS-based tools. </li><li>Analyze and synthesize data from multiple sources to support model parameterization, sensitivity testing, and robustness evaluation. </li><li>Collaborate closely with product, software, and client-facing teams to integrate model methodology into Verisk products. </li><li>Leverage Generative AI and agentic AI tools to accelerate modeling, prototyping, workflow automation, and insight generation. </li><li>Contribute to technical documentation and clearly communicate assumptions, methodology, limitations, and results. </li><li>Support client inquiries by explaining model behavior and outputs in a clear, practical, and accessible way. </li><li>Present analytical findings to both technical and non-technical audiences. </li></ul> <p>Required Qualifications</p> <ul> <li>Bachelor's or Master's degree in statistics, mathematics, data science, actuarial science, economics, engineering, computer science, or another quantitative/STEM field </li><li>At least 1 year of professional experience in data science, statistical modeling, risk modeling, or a related technical field </li><li>Strong programming skills in Python and SQL </li><li>Experience using Git-based development workflows </li><li>Experience working with AWS-based cloud analytics or data workflows </li><li>Demonstrated ability to take analytical or statistical models from proof-of-concept to implementation </li><li>Proven experience using AI-powered tools to support modeling, prototyping, automation, and productivity improvements </li><li>Strong written and verbal communication skills, with the ability to explain technical ideas to non-technical audiences </li></ul> <p>Nice to Have</p> <ul> <li>Familiarity with casualty or property insurance concepts (preferred but not required) </li></ul>