Job Description
Description About the Team The Enterprise Data & Data Science organization provides centralized product, platform, and technology support for Data Science teams across Liberty Mutual. Our team focuses on enabling the development, deployment, and adoption of AI/ML solutions through shared platforms, reusable capabilities, and enterprise-scale data science practices. We partner closely with Data Scientists, Engineers, Architects, and business stakeholders to accelerate innovation, improve operational efficiency, and help deliver business value through AI and machine learning. Description The Director, Data Science Product Management supports the organization, prioritization, and delivery of a portfolio of data science work that enables machine learning and AI solutions across Liberty Mutual. This role develops and drives product vision, represents the voice of the customer, and partners closely with Data Scientists, Engineers, Architects, and business stakeholders to deliver measurable business value. This role serves as the Product Owner for a portfolio of data science enablement capabilities, partnering with engineering teams to translate customer needs into prioritized roadmaps, backlogs, and delivered solutions. This role is ideal for a candidate who combines strong data science or technical expertise with product thinking and stakeholder leadership. Success requires the ability to understand the needs of Data Scientists, evaluate technical solutions, and translate complex technical concepts into product decisions and business outcomes. This position may be filled as an Assistant Director or Director I, Data Science based on experience. Asst Director, Data Science Product Management: $125,300 - $176,800 Dir I, Data Science Product Management: $142,800 - $201,300 Responsibilities Develop and drive product vision, roadmap, and prioritization for a portfolio of data science enablement capabilities. Develop business value estimates and success measures to inform prioritization and evaluate outcomes. Represent the voice of the customer and incorporate stakeholder feedback into product decisions. Partner with Data Scientists, Data Engineers, Software Engineers, and Architects to support the development, deployment, monitoring, and adoption of machine learning and AI solutions. Explore and evaluate technical solutions that improve model development, deployment, operational efficiency, and user experience. Drive the development and adoption of reusable patterns and platform capabilities that enable teams to more effectively deliver data science solutions. Partner with cross-functional teams to identify and prioritize technical debt reduction, DevOps, and MLOps improvements. Serve as Product Owner for assigned capabilities, developing, maintaining, and prioritizing product backlogs aligned to roadmap objectives and customer needs. Partner with delivery teams to support effective planning, execution, and delivery using Agile practices. Lead discussions, planning sessions, and stakeholder engagements for complex initiatives. Communicate product plans, priorities, recommendations, and outcomes to stakeholders and leadership. Qualifications Asst Director, Data Science Product Management- Bachelor`s degree in quantitative field with 5 to 7 years of related experience within insurance, actuarial, data science or technology product management. Master`s degree preferred. ACAS helpful. Dir I, Data Science Product Management- Bachelor`s degree in quantitative field with 7+ years, typically 10 or more years, of related experience within insurance, actuarial, data science or technology product management preferred. FCAS / ACAS preferred Master`s degree preferred Strong understanding of data science concepts, machine learning workflows, experimentation practices, and model lifecycle management. Demonstrated understanding of the end-to-end data science lifecycle, including model development, deployment, monitoring, and business value realization. Experience working directly with Data Scientists and partnering with Engineering and Architecture teams to deliver technical capabilities and business outcomes. Familiarity with model deployment, monitoring, experimentation, DevOps, and MLOps practices. Familiarity with modern data, analytics, and AI technologies (AWS, Azure, Databricks, etc.). Experience supporting enterprise AI/ML platforms, data science enablement capabilities, or model operationalization efforts. Demonstrated ability to evaluate technical solutions and translate complex data science, AI, and engineering concepts into actionable product decisions and business outcomes. Experience working effectively in large, complex, and highly matrixed organizations. Strong communication, stakeholder management, influence, and organizational leadership skills. 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
