Description The Sr Director I, Data Scientist will lead a team of experienced data scientists, people managers, and aligned MLOps teams focused on accelerating the deployment of data science models into production. This role will partner closely with data science, ML engineering, USRM IT, Enterprise Data and Data Science, and business stakeholders to advance Liberty Mutual’s model deployment and MLOps capabilities. This leader will help shape strategy, roadmaps, and priorities that improve the speed, reliability, scalability, and governance of non-pricing model deployments across USRM. The role is responsible for driving cross-functional execution, managing technical backlogs and team priorities, and ensuring deployed solutions align with Frontiers broader technology transformation efforts. Key Responsibilities: Lead, manage, coach, and develop a team of data science, MLOps, and people leaders. Define and execute strategies to improve model deployment capabilities across multiple P&L verticals. Partner with USDS, USDS Infrastructure, ML Engineering, USRM IT, Enterprise Data and Data Science, and business stakeholders to deliver scalable model deployment solutions. Drive the prioritization and management of ML engineering backlogs, model deployment requests, and new feature development. Ensure current and future deployment solutions align with enterprise technology transformation initiatives, such as Frontier, and with architecture standards. Collaborate with internal stakeholders to improve MLOps practices, deployment workflows, model governance, and operational efficiency. Support deployment of models using internal tools and platforms, such as Runway, and help expand adoption of standardized deployment processes. Influence stakeholders and senior leaders through clear communication of strategy, progress, risks, and recommendations. Stay current on developments in data science frameworks, model orchestration, MLOps, and deployment automation. Qualifications Deep knowledge of predictive analytics techniques and statistical diagnostics of models. Strong understanding of data science workflows, model lifecycle management, and MLOps concepts. Expert knowledge of predictive toolsets and technical analytics platforms. Proven ability to lead teams and drive complex projects to completion through others. Prior experience managing and developing talent. Strong collaboration skills with the ability to work effectively across technical and business teams. Excellent verbal, written, and presentation skills, with the ability to communicate complex ideas clearly and concisely. Ability to build relationships and influence stakeholders at multiple levels of the organization. Ability to use analysis and business insight to support recommendations and drive decisions. Competencies typically acquired through an advanced degree in Statistics, Mathematics, Data Science, Computer Science, or a related field and 8 years of relevant experience, including leadership experience in data science, analytics, or MLOps, or may be acquired through a Bachelor’s degree (scientific field of study) and 10 years of relevant experience. Equivalent combination of education and experience may be considered. Insurance or financial services industry experience preferred. Travel 10%