Director, Data Science Rollout AI

Liberty Mutual•Boston, MA

About The Position

US Data Science (USDS) is seeking a Director-level data science leader to build and lead a new team focused on using advanced AI to bring insurance pricing programs to market faster. The team will develop evaluations for AI and agentic systems to measure the value they deliver, their accuracy, and the risks associated with errors, enabling high-value applications to move into production with confidence. This highly visible role will shape the use of AI in USRM’s core pricing work. The Director will lead senior data scientists aligned with USRM business lines and establish a shared evaluation strategy. The role sets the roadmap for applying AI to pricing rollout, leads the design of evaluations, measures business value, partners with teams developing AI applications, and objectively evaluates vendors and third-party solutions. The ideal candidate combines strong people leadership and insurance pricing experience with hands-on expertise in modern AI and LLMs. Candidates within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will work a hybrid schedule, in the office two days per week. Otherwise, the role is remote with occasional travel. The typical starting salary range depends on factors such as skills, experience, education, certifications, and location; the posting does not provide specific salary figures.

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; prior experience effectively managing talent.
Exceptional stakeholder management and a track record of driving outcomes across teams the candidate does not own.
Deep expertise in model evaluation, statistics, experimental design, predictive analytic techniques, and statistical diagnostics of models.
Strong, recent hands-on experience with modern LLMs, including agentic coding, incorporating 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.
Ability to turn data science and AI strategy into a prioritized roadmap.
Ability to lead and drive projects and assignments to completion through others.
Ability to communicate complex information clearly and concisely, verbally, visually, and in writing, for different audiences and stakeholders.
Ability to establish relationships within and outside the aligned functional area or strategic business unit, and to give effective training and presentations to management and other groups.
Broad knowledge of business drivers and market context, with a value-driven perspective on work context and impact.
Bachelor’s degree in a quantitative field with 10 or more years of related experience in insurance, actuarial, data science, or technology; alternatively, a master’s degree with at least 8 years of relevant experience. The posting also describes competencies typically acquired through an advanced degree in a relevant field plus 5–7 years of relevant experience, or a bachelor’s degree in a scientific field plus 10 years of relevant experience.
Resilient and curious, committed to finding the best answer, and holds themselves to a high standard.

Nice To Haves

Experience evaluating generative AI or agentic systems.
Insurance or financial services industry 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—while 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 evaluations for AI and agentic systems, including defining accuracy metrics and ground truth, designing statistical tests and experiments, and tailoring evaluation depth 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 data science, technology, and pricing delivery teams building AI to incorporate evaluation early and help high-value applications reach production.
Support evaluations of AI vendors and third-party solutions by providing objective, data-science-based assessments of their capabilities.
Lead and develop high-performing technical teams and drive projects to completion through others.
Communicate complex work clearly to senior leaders and other stakeholders, including through presentations and exhibits.
Build relationships within and outside the aligned functional area or strategic business unit, and provide effective training and presentations to management and other groups.