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

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: Ernst & Young Oman
Full Time position
Listed on 2026-01-03
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 205000 - 235000 USD Yearly USD 205000.00 235000.00 YEAR
Job Description & How to Apply Below
Position: EY-Parthenon - Strategy and Execution - Growth Platforms - Product Manager - Director

Location:

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.

EY-Parthenon – EY Growth Platforms - AI Product Management - Director

EY-Parthenon’s unique combination of transformative strategy, transactions and corporate finance delivers real-world value – solutions that work in practice, not just on paper. Benefiting from EY’s full spectrum of services, we’ve reimagined strategic consulting to work in a world of increasing complexity.

With deep functional and sector expertise, paired with innovative AI-powered technology and an investor mindset, we partner with CEOs, Boards, Private Equity and Governments every step of the way – enabling you to shape your future with confidence.

Within the EY-Parthenon service line, the EY Growth Platforms AI Product Management Director will collaborate with Business Leaders, AI/ML Engineers, Data Scientists, Project Managers, and other team members to design, build, and scale innovative AI solutions that power strategic growth initiatives and create enterprise value for F500 clients.

The opportunity

The EY Growth Platforms AI Product Management Director will play a critical role leading the development of data-driven, AI-powered agent applications that surface strategic insights across industries like insurance, CPG, and demand forecasting. You’ll work with engineering leads to build multi-source insight workflows and with business stakeholders to translate customer needs into functional product specs, agent behavior, and user experiences (API, dashboard, or embedded AI).

Your

key responsibilities
  • 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 Dev Ops/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
  • A bachelor's degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or other related field and 5 years of related work experience; or a graduate degree and approximately 3 years of related work experience
  • 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.
  • Experience working in a startup and/or management/strategy consulting.
  • Knowledge of how to leverage AI tools in a business…
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