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# Director, Data Science Rollout AI

- **Company:** Liberty Mutual Insurance Company
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $156,000.0 - $281,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Statistical Hypothesis Testing, Python (Programming Language), Retrieval-Augmented Generation, Large Language Models, Model Validation
- **Published:** October 25, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=66b824126257060c

## About the Role

* Hands-on experience building and deploying insurance pricing models, with an end-to-end understanding of the pricing lifecycle from model build through filing and implementation.
 * Proven experience leading and developing high-performing technical teams.
 * Exceptional stakeholder management, with a track record of driving outcomes across teams you do not own and explaining complex work clearly to senior leaders.
 * Deep expertise in model evaluation, statistics, and experimental design.
 * Strong, recent hands-on experience with modern LLMs, including but not limited to agentic coding, building LLMs into applications, and RAG.
 * Experience evaluating generative AI or agentic systems is strongly preferred.
 * Hands-on technical skills (for example, Python) strong enough to prototype evaluation tooling and credibly review the work of engineering teams.
 * Demonstrated ability to turn data science and AI strategy into a prioritized roadmap.
 * Bachelor's degree in a quantitative field with 10+ years of related experience within insurance, actuarial, data science, or technology preferred, or a Master's degree plus 8 years of relevant experience.
 * Resilient, curious, acts in service of the best answer, holds themselves to a high standard and wants to be around others who do the same., * Deep knowledge of predictive analytic techniques and statistical diagnostics of models.
 * Expert knowledge of predictive toolset, to include highly technical tools.
 * Proven ability to lead and drive projects and assignments to completion through others, to include prior experience effectively managing talent.
 * Demonstrated ability to exchange ideas and convey complex information clearly and concisely, verbally, visually (presentations and exhibits), and in writing, consistent with the audiences and stakeholders with which s/he interacts.
 * Ability to establish and build relationships within and outside the aligned functional area or SBU. Ability to give effective training and presentations to management and other groups.
 * Presents to senior or functional department leaders or executives.
 * Broad knowledge of business drivers and market context.
 * Has a value driven perspective with regard to understanding of work context and impact.
 * Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) and 5 to 7 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) with 10 years of relevant experience.
 * Insurance or financial services industry experience preferred.

## Description

* Build and lead a team of senior data scientists, each partnered with one of USRM's lines of business (Property & Specialty, Auto, and Small Commercial) and working from a shared evaluation strategy.
 * Set the strategy and roadmap for how USDS uses AI to accelerate pricing program rollout, focused on the use cases with the highest value and risk.
 * Lead the design of state-of-the-art AI and agentic evaluations. Define accuracy metrics and ground truth, design statistical tests and experiments, and match the depth of evaluation to the stakes of each use case.
 * Measure the value of AI applications, including effort reduced, errors avoided, and time to market gained, and help leaders decide what to scale.
 * Partner with the data science, technology, and pricing delivery teams building AI to bring evaluation in early and help high-value applications reach production.
 * Support evaluations of AI vendors and third-party solutions, giving an objective, data-science-based assessment of what they can deliver.