Product Owner - Advanced Analytics & Research

Be Here. Be Great. Working for a leader in the insurance industry means opportunity for you. Great American Insurance Group's member companies are subsidiaries of American Financial Group. We combine a "small company" culture where your ideas will be heard with "big company" expertise to help you succeed. With over 30 specialty and property and casualty operations, there are always opportunities here to learn and grow. At Great American, we value and recognize the benefits derived when people with different backgrounds and experiences work together to achieve business results. Our goal is to create a workplace where all employees feel included, empowered, and enabled to perform at their best. P&C IT Services provides professional services to help our business units and corporate functions use technology to create, manage, and optimize information and business processes.  IT Services can include a wide range of activities such as: software development, data management, Cloud services, IT security, network security, technical support, establishing and overseeing access rights, procuring and maintaining equipment or software, managing the infrastructure, and defining security procedures,  The overall goal of IT Services is to provide technology solutions that increase efficiency, reduce costs, and give our company a competitive advantage over our competitors. Great American’s culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are expected to be on-site a minimum of two days a week if local to Cincinnati, with the potential to work three days remotely. Core in‑office days are Tuesday and Thursday but will be determined by business needs.  As the insurance industry undergoes digital transformation, the AI Innovation Lab serves as Great American’s proving ground for emerging AI capabilities. Team members evaluate, prototype, and   validate   AI technologies against   real business   needs,   determining   what’s   ready for enterprise adoption and what   isn’t . This is applied   research   with a purpose: every initiative ties directly to business requests, and successful   proofs-of -concept are handed off to IT delivery teams for production implementation.    What Makes This Role Unique   This   isn’t   a traditional research position, and it   isn’t   a traditional development role.   It’s   something in between—now with senior product ownership and change leadership:   Vision-to-value ownership: You create and evolve the Lab’s product vision and   roadmap   so work stays tightly aligned to enterprise priorities and measurable outcomes.    Rapid experimentation:   You’ll   go deep on   a technology , guide the team to build working prototypes,   determine   fit-for-purpose, and move to the next challenge.    Business-driven focus: Every project originates from   a real business   ask—supporting underwriters, actuaries, claims professionals, and analysts across the enterprise.    Fail-fast culture: A well-documented “no, and here’s why” is as valuable as a successful proof-of-concept.    Partnership model to production: You work with Enterprise Architecture and IT delivery   teams   so innovations can be operationalized—not just demoed.    Human-in-the-loop philosophy: Ethical, transparent, explainable AI is foundational in insurance; you ensure designs reflect that from day one.    Key Responsibilities   1) Vision Creation & Product Strategy   Define and communicate the AI Innovation Lab product vision, outcomes, and success metrics;   maintain   a roadmap that balances innovation with enterprise readiness.    Create decision frameworks for   adopt   /   adapt   / defer /   reject   outcomes so the Lab’s learning directly informs enterprise AI strategy.    Own prioritization of initiatives across multiple business requests based on value, feasibility, risk, and operational constraints.    2) Customer Engagement (Business Stakeholders) & Executive Communication   Serve as the primary Lab-facing leader for business stakeholders and executives: intake, discovery, expectation-setting, and ongoing engagement.    Translate ambiguous business asks into clear problem statements, hypotheses, and acceptance criteria for research and prototypes.    Deliver clear, credible readouts—able to explain tradeoffs, risks, and readiness to both technical and non-technical audiences.    3) Product Design & Research Planning   Drive product discovery: user journeys, workflow design, guardrails, human-in-the-loop controls, and measurable definitions of value.    Partner with technical team members to ensure prototypes align with enterprise constraints and API-first integration principles.    Ensure evaluation plans exist before building (quality measures, go/no-go criteria, and what “good” looks like).    4) Research Delivery & Transition to Production   Oversee rapid prototypes and   proofs-of-concept   from   concept through stakeholder validation; ensure learnings are documented (wins and failures).    Coordinate with Enterprise Architecture and IT delivery teams to shape handoffs that can succeed in production (security, operations, integration, support model).    Ensure the Lab produces “decision-grade” outputs: feasibility, limitations, risk, and a recommended path forward.    5) Full-Stack AI Lifecycle Ownership & Optimization   Demonstrated understanding of the full AI product lifecycle: problem framing → data readiness → model/approach selection (ML vs GenAI) → prototyping → evaluation → governance/security → production transition → monitoring and continuous improvement.    Drive optimization across performance, cost, and reliability: latency/throughput, retrieval quality (RAG), prompt/agent instruction tuning, and regression   control as   systems evolve.    Champion   MLOps / LLMOps   practices: reproducibility, versioning (models/prompts), CI/CD patt