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Salary
$180k – $319k per year (Estimated)
Location
In office (New York)
Seniority
Senior · 7+ years exp
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Join the Consumer & Community Banking Data & Analytics Unstructured Data Products team and unlock the value of documents, conversations, images, audio, video, and other multimodal data for analytics and AI. Our mission is to turn unstructured data into trusted, governed, and reusable enterprise assets that enable meaningful business outcomes and prepare Consumer & Community Banking for an AI-enabled future.

As a Product Owner in the Consumer & Community Banking (CCB) Data & Analytics Unstructured Data Products team, you will define the strategy for unstructured data product development and build the partnerships needed to deliver value with data across the firm.

Job Responsibilities

  • Define and champion the strategy, vision, roadmap, and priorities for unstructured data products across CCB.
  • Partner with business leaders and Data Owners to identify high-value opportunities and turn them into governed, reusable data products.
  • Build coalitions across business, product, data, technology, risk, and control teams to move opportunities from concept through adoption.
  • Lead consultative discovery, translating ambiguous business challenges into clear product concepts, value propositions, and actionable plans.
  • Develop compelling executive narratives, business cases, and demonstrations that establish urgency and secure stakeholder support.
  • Guide multidisciplinary teams in building scalable capabilities and standards for publishing, discovering, and consuming AI-ready unstructured data.
  • Lead lighthouse products and pilots, measure adoption and business value, and apply learnings to accelerate reuse across CCB.
  • Ensure products and operating models meet applicable governance, privacy, compliance, records management, risk, and control requirements.

Required Qualifications, Capabilities, and Skills

  • 7+ years of experience in product management, strategy, consulting, data, technology transformation, data science, or a related field.
  • Demonstrated ability to turn ambiguous, complex problems into clear strategies, actionable roadmaps, and measurable outcomes.
  • Strong strategic thinking and product leadership skills, including opportunity discovery, prioritization, experimentation, delivery, adoption, and value measurement.
  • Exceptional executive communication and storytelling skills, with the ability to simplify complex topics and build support among technical and non-technical audiences.
  • Proven ability to build trusted relationships, influence without authority, and align senior stakeholders across business, data, technology, risk, and control organizations.
  • Technical fluency in unstructured data and AI, with the ability to translate emerging capabilities, constraints, and governance requirements into practical product decisions.
  • Working knowledge of unstructured data pipelines, data product interfaces, metadata, taxonomy, search, retrieval, chunking, indexing, evaluation, and governance, including how these capabilities affect AI-enabled experiences.

Preferred Qualifications, Capabilities, and Skills

  • Experience in consulting, financial services, enterprise data, or technology industries.
  • Master's degree in business, computer science, information science, data science, or a related discipline.
  • Experience using AI productivity tools, connectors, agent skills, workflow automation, or context-curation techniques to improve organizational effectiveness.
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