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.
