Director I, Data Science, Enterprise Data & Data Science

Description We're seeking an exceptional, hands-on Data Scientist with deep expertise in data science, MLOps, and building GenAI solutions to join our Enterprise Data & Data Science team. In this role, you'll identify, evaluate, and develop solutions at the intersection of data science, generative AI, and enterprise data strategy—including GenAI evaluation frameworks and semantic data layers. You'll also serve as a community champion, driving the adoption of best practices across a large, collaborative data science organization. Responsibilities : Design, build, and evaluate generative AI solutions and agentic systems Develop and maintain data semantic layers and knowledge graphs for enterprise-scale data accessibility Build evaluation frameworks and tools to assess GenAI systems' performance, reliability, and safety Collaborate with other data scientists, machine learning engineers, data engineers, and business partners Champion best practices and tooling across a broad data science community Lead cross-functional working groups and contribute to innovation in AI/ML methods Communicate complex technical findings clearly to non-technical stakeholders Serve as a technical consultant on complex, high-impact projects Please note this is an individual contributor role Qualifications Broad knowledge of predictive analytic techniques and statistical diagnostics of models. Advanced knowledge of predictive toolset; reflects as expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Ability to establish and build relationships within and outside the organization. Ability to give effective training and presentations to management and other groups. Ability to use results of analysis to persuade team, department management or senior management to a particular course of action. 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 a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of 8 years of relevant experience. Preferred Experience: Strong foundation in data science and machine learning Proven MLOps expertise across the complete data science lifecycle Experience building GenAI solutions and agentic systems Familiarity with GenAI evaluation methodologies Experience with data semantic layers and/or knowledge graphs Track record of cross-functional collaboration in a large enterprise environment Ability to work ET hours  About Us Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role. At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays