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Liberty Mutual

Data Science Product Manager

Boston, MA, United States
Portsmouth, NH, United States

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Job details

Apply by: Nov 9, 2027
Posting language: English
Posted: Nov 9, 2024

Original job description

Description Join AI Products and Transformation (APT) | Data Science Solutions and help our team shape how AI transforms underwriting at scale. We’re looking for a Data Science Product Manager to lead the strategy, development, and scaling of AI-powered intelligence products changing how underwriters make decisions. This role sits at the intersection of underwriting, product management, data science, and technology, with the opportunity to take successful solutions and expand them across North America underwriting segments, profit centers, and lines of business. You’ll lead high-visibility decision intelligence products leveraging machine learning, Generative AI, and Agentic AI to help underwriters make faster, more informed decisions. You’ll work directly with business leaders, data scientists, engineers, architects, and technology partners to identify high-value opportunities, shape product strategy and roadmaps, and turn emerging intelligence capabilities into scalable solutions with measurable business impact. This is a great opportunity for someone who enjoys building and scaling innovative AI products, solving complex business problems, and influencing how a large underwriting organization works in the future.

Role Summary

The Data Science Product Manager will lead the strategy, development, deployment, and scaling of complex intelligence products that leverage machine learning, Generative AI, and Agentic AI technologies to improve underwriting decision-making and business outcomes. This role is responsible for driving the expansion and adoption of successful intelligence products across underwriting segments, profit centers, and lines of business, maximizing reuse, consistency, and enterprise impact.

Additionally, this role partners across business, data science, and technology teams to identify opportunities, prioritize investments, and deliver scalable solutions that create measurable value.

Responsibilities

Product Strategy & Vision

Define and drive strategy for advanced analytics products, multi-year roadmaps, and investment priorities for a portfolio of enterprise intelligence products.
Identify high-value opportunities where AI, machine learning, Generative AI, and decision intelligence capabilities can create measurable business impact.
Establish product vision, success metrics, and adoption strategies aligned to organizational and enterprise objectives.
Drive product portfolio decisions through business case development, financial valuation, and outcome-based prioritization.

AI & Data Science Product Leadership

Partner with Data Scientists, Engineers, Architects, and Technology teams to deliver scalable AI and machine learning solutions throughout 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 with engineering partners on production deployment strategies, MLOps processes, observability, model monitoring, reliability, and governance.
Influence technical direction on AI platform capabilities, reusable services, model orchestration, and enterprise-scale intelligence architecture.

Stakeholder & Customer Leadership

Serve as the voice of the customer and trusted advisor to business leaders, translating complex business challenges into scalable product solutions.
Build alignment across senior stakeholders while effectively managing competing priorities, trade-offs, dependencies, and resource constraints.
Communicate complex technical concepts, AI capabilities, and product outcomes to both technical and non-technical audiences, including executive leadership.
Drive organizational readiness, training, adoption, and change management activities to maximize business value realization.

Portfolio Management & Delivery

Own product valuation frameworks, prioritization methodologies, and outcome measurement processes.
Define, measure, and communicate KPIs related to business outcomes, adoption, operational efficiency, profitability, and product performance.
Lead product planning activities, including roadmap development, PI planning, dependency management, and release coordination.
Guide identification and prioritization of technical debt, platform modernization, and product scalability initiatives.

Governance, Risk & Responsible AI

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 robust monitoring, auditability, explainability, and feedback mechanisms across AI-powered solutions.
Establish frameworks for evaluating, measuring, and continuously improving model and GenAI performance.

Qualifications

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 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.
Experience translating business needs into product strategy and prioritizing work based on customer and business value.
Strong communication, relationship-building, 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 both technical and non-technical audiences.
Proficiency with analytical and advanced analytics product management tools including PowerPoint, SQL, Python, modern data and AI technologies.
Understanding of insurance underwriting practices, risk assessment, pricing, and decision-support workflows preferred.
Experience building, deploying, or scaling GenAI, agentic, or advanced analytics solutions preferred.
ACAS or equivalent insurance industry credentials helpful.

Preferred Experience

Strong foundation in data science, machine learning, and AI technologies.
Strong advanced analytics product management experience supporting complex intelligence products.
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.

Qualifications

Responsible for the management, technical oversight and development for a team of data science and advanced analytics staff.
Collaborates with business partners to develop tools and services such as modeling, dashboard development, and decision aids to drive strategic decision making.
Presents findings, shares insights, and makes recommendations that impact profitability, growth and/or customer satisfaction.
Provides tactical input on highly technically complex projects that drive change across function, SBU or Corporate Department.
Supervises and performs highly complex well-defined work, containing technical and creative predictive analytics projects.
Regularly engages with the data science community and leads cross functional working groups.

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 a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve. We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/BenefitsLiberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.Fair Chance Notices

California
Los Angeles Incorporated
Los Angeles Unincorporated
Philadelphia
San Francisco

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More about this job

Skills

Machine learning
Underwriting
Decision making
Develop business case
Prioritization
Leadership
Change management
Risk management
ML
Communication skills
Relationship building
Stakeholder management
Microsoft PowerPoint
SQL
Python
Hazard assessment
Collaboration
Customer service

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