Data Science Product Manager

About the job

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. Guide 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. Establish frameworks for evaluating, measuring, and continuously improving model and GenAI performance. 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. 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. 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. 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. 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.