Data Science Product Manager

Liberty Mutual is building AI-powered intelligence products to strengthen underwriting decision-making. As a Data Science Product Manager in Boston, you will help shape the strategy, roadmap, and execution of advanced analytics capabilities using machine learning, Generative AI, and agentic approaches, partnering closely with business, data science, and technology teams to deliver measurable business impact. The role sits onsite in Boston, MA and offers a competitive salary range of USD 137,000 - 257,000 per year.

What you will do

• Define and drive strategy for advanced analytics products, including multi-year roadmaps and investment priorities across a portfolio of enterprise intelligence products.
• Identify high-value opportunities where AI, machine learning, Generative AI, and decision intelligence capabilities can create measurable business outcomes.
• Set product vision, success metrics, and adoption strategies aligned to enterprise and organizational goals.
• Guide portfolio decisions using business cases, financial valuation, and outcome-based prioritization.
• Partner with Data Scientists, Engineers, Architects, and technology teams to deliver scalable AI and machine learning solutions across the full product lifecycle.
• Lead the development and deployment of advanced AI capabilities, including predictive modeling, NLP, LLM-powered applications, RAG architectures, agentic workflows, recommendation engines, and decision intelligence solutions.
• Collaborate on production deployment strategies, including MLOps processes, observability, model monitoring, reliability, and governance.
• Influence technical direction for AI platform capabilities, reusable services, model orchestration, and enterprise-scale intelligence architecture.
• Act as the voice of the customer and a trusted advisor to business leaders, translating complex business challenges into scalable product solutions.
• Drive alignment across senior stakeholders while managing competing priorities, trade-offs, dependencies, and resource constraints.
• Communicate product outcomes and complex technical concepts to technical and non-technical audiences, including executive leadership.
• Drive organizational readiness, training, adoption, and change management to maximize business value realization.
• Own product valuation frameworks, prioritization methodologies, and outcome measurement processes, including KPIs for business outcomes, adoption, operational efficiency, profitability, and product performance.
• Lead product planning activities such as roadmap development, PI planning, dependency management, and release coordination.
• Direct identification and prioritization of technical debt, platform modernization, and product scalability initiatives.
• Ensure intelligence products are designed and operated in accordance with Responsible AI principles, governance standards, model risk management practices, and regulatory requirements.
• Partner with governance and technology teams to implement monitoring, auditability, explainability, and feedback mechanisms across AI-powered solutions.
• Establish evaluation and continuous improvement frameworks for model and GenAI performance.
• Provide management, technical oversight, and development for a team of data science and advanced analytics staff.
• Collaborate with business partners to deliver tools and services such as modeling, dashboard development, and decision aids that support strategic decision-making.
• Present findings, share insights, and recommend actions that impact profitability, growth, and/or customer satisfaction.
• Provide tactical input on highly technical projects that drive change across functions, SBU, or corporate departments.
• Supervise and perform highly complex work involving technical and creative predictive analytics projects.
• Engage with the data science community and lead cross-functional working groups on an ongoing basis.

What you bring

• Bachelor’s or Master’s degree in a quantitative field with 5+ years of experience in insurance, actuarial, data science, analytics, technology, or advanced analytics product management.
• Prior advanced analytics product management experience supporting data science, machine learning, AI, or intelligence solutions is preferred.
• Strong understanding of data science, machine learning, Generative AI, and agentic AI concepts and methodologies.
• Knowledge of data science product development, deployment, MLOps, monitoring, and governance practices.
• Understanding of technology platforms, architectures, APIs, and tools used to support AI/ML solutions.
• Ability to translate business needs into product strategy and prioritize work based on customer and business value.
• Strong communication and stakeholder management skills, including the ability to influence senior leaders and drive alignment across functions.
• Ability to communicate technical concepts and analytical findings to technical and non-technical audiences.
• Proficiency with analytical and advanced analytics product management tools including PowerPoint, SQL, and Python, as well as modern data and AI technologies.
• Insurance underwriting practices, risk assessment, pricing, and decision-support workflows are preferred.
• Experience building, deploying, or scaling GenAI, agentic, or advanced analytics solutions is preferred.
• ACAS or equivalent insurance industry credentials are helpful.
• Proven experience scaling successful solutions across multiple business segments, underwriting organizations, or product lines.
• Experience with MLOps, AI governance, model monitoring, and enterprise deployment practices.
• Experience building GenAI solutions, RAG applications, and agentic systems.
• Familiarity with GenAI evaluation methodologies and Responsible AI principles.
• Track record of cross-functional collaboration and leadership within a large enterprise environment.
• Experience driving adoption and value realization for AI-enabled products at scale.

Tools and technologies you will work with

• Machine learning, Generative AI, Agentic AI, NLP, LLM-powered applications, RAG architectures, agentic workflows, recommendation engines, decision intelligence solutions
• MLOps, observability, model monitoring, governance
• Responsible AI, PowerPoint, SQL, Python, APIs

Pay philosophy

• The typical starting salary range is determined by factors including skills, experience, education, certifications, and location.
• The full salary range reflects competitive labor market value for these positions across the national market and provides opportunity to progress as employees grow and develop within the role.
• Some roles at Liberty Mutual may include a corresponding compensation plan with commission and/or bonus earnings, based on factors set forth in that plan.

Benefits

To learn more about Liberty Mutual benefit offerings, visit: https://LMI.co/Benefits

Fair chance notices: California; Los Angeles Incorporated; Los Angeles Unincorporated; Philadelphia; San Francisco.