EY-Parthenon - Strategy and Execution - Growth Platforms - Product Manager - Director

• Location: New York, Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle
• At EY, we’re all in to shape your future with confidence.
• We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.  Join EY and help to build a better working world.
• Your key responsibilities
• Skills and attributes for success
• Drive end-to-end development of agentic products that combine internal, public, and licensed third-party data.
• Translate ambiguous business goals into clearly defined agent roles, workflows, data requirements, and interface specs.
• Own product roadmap and use case prioritization based on technical feasibility, customer impact, and data availability.
• Collaborate with AI/ML Engineers to validate model fit, feature strategy, and insight generation logic.
• Work with Data Engineers to assess data availability, coverage, and merge logic across insurance, consumer, market, sector and macroeconomic signals.
• Partner with DevOps/Platform teams to ensure secure, scalable, compliant delivery of outputs (dashboards, APIs, notebooks, or alerts).
• Define POC and MVP requirements and success metrics for each agent product or data application.
• Own customer-facing positioning of agent capabilities: “What does this AI agent know? How does it help solve a specific business problem?”
• To qualify for the role, you must have
• Product management experience, ideally in data-intensive or AI/ML-driven platforms.
• Strong experience and understanding of data product lifecycle — ingestion, cleaning, merging, modeling, serving.
• Proven experience leading products that sit at the intersection of business insight, data science, and engineering.
• Strong understanding of real-world structured data merging, schema linking, and model evaluation at scale.
• Familiarity with the concepts behind agentic AI workflows, RAG, or data fusion for insight delivery.
• Ability to communicate clearly across technical and non-technical stakeholders — from model latency to customer value.
• Deep comfort working with multi-sector data — e.g., insurance filings, economic indicators, behavioral signals.
• The ability and willingness to travel and work in excess of standard hours when necessary.
• Ideally, you’ll also have
• Experience deploying AI/ML products or features into a production.

None flagged.