Director, Data Science Rollout AI

Liberty Mutual Insurance•Boston, MA

2d•$156,000 - $281,000•Hybrid

About The Position

US Data Science (USDS) is seeking a Director-level data science leader to build and lead a new team applying advanced AI to accelerate insurance pricing program rollouts. The team will develop evaluations for AI and agentic systems to measure delivered value, accuracy, and risk, enabling high-value applications to move into production with confidence. This highly visible team will shape how AI is used in USRM’s core pricing work. The ideal candidate combines strong people leadership with deep hands-on experience building and deploying insurance pricing models and applying modern AI and LLMs. The role may have in-office requirements depending on the candidate’s location. Candidates living within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX follow a hybrid schedule, working in the office two days per week. Otherwise, the role is remote with occasional travel.

Requirements

Hands-on experience building and deploying insurance pricing models, with 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, including driving outcomes across teams outside the candidate’s ownership and clearly explaining complex work to senior leaders.
Deep expertise in model evaluation, statistics, and experimental design.
Strong, recent hands-on experience with modern LLMs, including agentic coding, integrating LLMs into applications, and retrieval-augmented generation (RAG).
Hands-on technical skills, such as Python, sufficient to prototype evaluation tooling and credibly review engineering teams’ work.
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 in insurance, actuarial work, data science, or technology preferred, or a master’s degree with 8 years of relevant experience.
Deep knowledge of predictive analytic techniques and statistical diagnostics of models.
Expert knowledge of predictive tools, including highly technical tools.
Ability to lead and drive projects and assignments to completion through others, including effectively managing talent.
Ability to communicate complex information clearly and concisely verbally, visually, and in writing, in ways appropriate to the audiences and stakeholders involved.
Ability to establish and build relationships within and outside the aligned functional area or strategic business unit, and to provide effective training and presentations to management and other groups.
Ability to present to senior or functional department leaders or executives.
Broad knowledge of business drivers and market context, and a value-driven understanding of work context and impact.
Resilience, curiosity, a commitment to finding the best answer, high personal standards, and a desire to work with others who hold themselves to high standards.

Nice To Haves

Experience evaluating generative AI or agentic systems.
Insurance or financial services industry experience.
An advanced degree in Statistics, Mathematics, Data Science, or a relevant field with 5 to 7 years of relevant experience, or a bachelor’s degree in a scientific field with 10 years of relevant experience.

Responsibilities

Build and lead a team of senior data scientists, each partnered with a USRM line of business—Property & Specialty, Auto, or Small Commercial—and working from a shared evaluation strategy.
Set the strategy and roadmap for using AI to accelerate pricing program rollout, prioritizing use cases with the highest value and risk.
Lead the design of AI and agentic system evaluations, including defining accuracy metrics and ground truth, designing statistical tests and experiments, and tailoring evaluation depth to each use case’s stakes.
Measure the value of AI applications, including effort reduced, errors avoided, and time to market gained, and help leaders determine what to scale.
Partner with data science, technology, and pricing delivery teams to bring evaluation into AI development early and help high-value applications reach production.
Support evaluations of AI vendors and third-party solutions by providing objective, data-science-based assessments.