Product Owner, Unstructured Data & AI – Vice President
Join the Data and Analytics Unstructured Data Product team where you will help turn multimodal documents, conversations, images, audio, and video into trusted, reusable assets.
As a Product Owner, within the Consumer and Community Banking Team, you will set product strategy and lead development of capabilities that make unstructured data discoverable, governed, and AI-ready and partner with leaders to frame complex problems, translate business needs into product requirements, and guide multidisciplinary teams from discovery through adoption.
Job Responsibilities:
Partner with senior leaders across CCB Lines of Business to identify high-value problems, clarify desired outcomes, and develop practical strategies for using knowledge and unstructured data to improve customer and employee experiences.
Own the product vision, multi-year roadmap, and prioritized backlog for unstructured data products, translating business outcomes into clear capabilities, requirements, acceptance criteria, and deliverables.
Lead consultative discovery with business, product, data, technology, risk, and control partners; synthesize differing perspectives, challenge assumptions, and convert ambiguous needs into clear problem statements, recommendations, and decisions.
Build compelling executive narratives, business cases, presentations, and demonstrations that explain complex concepts simply, establish urgency, and secure support for the team's vision and priorities.
Build reusable capabilities for ingesting, extracting, enriching, classifying, publishing, discovering, retrieving, and evaluating unstructured data across documents, transcripts, images, audio, and video and define product expectations for metadata, quality, lineage, access, interfaces, lifecycle, and service levels so unstructured data can be consumed reliably by applications, analytics, search, and AI agents.
Create durable partnerships and engagement models across CCB, including stakeholder forums, working sessions, playbooks, and enablement programs that help Lines of Business adopt shared capabilities and publish reusable data products.
Identify opportunities for AI-assisted tool use and automated workflows; lead pilots, define success measures, gather evidence, and recommend whether to stop, refine, or scale each solution and ensure solutions and operating models meet the firm's risk, controls, compliance, privacy, records-management, and regulatory requirements.
Required Qualifications, Capabilities, and Skills
Bachelor's degree or equivalent experience, plus 7+ years of product management experience owning delivery in complex, cross-functional environments demonstrating success solving ambiguous business problems by structuring the analysis, evaluating options and tradeoffs, and turning recommendations into action.
Strong executive communication and storytelling skills, including the ability to distill complex subjects into clear narratives, recommendations, roadmaps, presentations, and decision materials for technical and non-technical audiences.
Technical fluency in unstructured data and AI products, with the ability to collaborate credibly with engineers, architects, data scientists, and governance partners and translate technical possibilities and constraints into product choices.
Proven ability to build trusted relationships, influence without direct authority, and align senior stakeholders across business and technical organizations with competing priorities.
Strong command of product development practices, including customer discovery, problem definition, prioritization, roadmaps, experimentation, iterative delivery, adoption, and value measurement.
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, banking, or technology industries.
Master's degree in business, computer science, information science, knowledge representation, data science, or a related discipline.
Experience using AI productivity tools, connectors, agent skills, workflow automation, or context-curation techniques to improve team effectiveness.