What are the responsibilities and job description for the Asset & Wealth Management - Product Manager, Applied AI & Data Products - Vice President position at JPMorgan Chase?
Own a high-impact portfolio of unified data products—spanning applied AI, advanced analytics, visualization, and regulatory solutions—powered by the Global Private Bank’s federated data mesh.
The Analytics & Applied AI team within the Chief Data & Analytics Office (CDAO) of the Global Private Bank is responsible for unified data products — data products that cut across multiple core data domains — delivered through a multi-pod model and underpinned by the federated data mesh and its distribution points. The team's capabilities span applied AI, advanced analytics, data visualization, and regulatory and compliance data products, all aligned to the broader data mesh strategy.
As the Product Manager within the Chief Data & Analytics Office you will own the product strategy and delivery for a portfolio of unified data products spanning applied AI, analytics and visualization, and regulatory and compliance domains. The role is a balanced blend of general product management craft — vision, roadmap, backlog, discovery, metrics, and stakeholder management — with hands-on ownership of specific key initiatives across the portfolio.
This is an AI-forward product management role. We’re seeking a leader who consistently applies AI and large language model (LLM) tools both in the products they build and in their day-to-day product management practice—using them to speed up discovery, clarify requirements, accelerate prototyping, and streamline delivery, while shipping intelligent, AI-enabled data products.
Job Responsibilities
- Define and own the product vision, strategy, and multi-quarter roadmap for the assigned portfolio of data products
- Own and prioritize the product backlog; write clear requirements and user stories; partner with engineering and scrum leads on delivery
- Conduct customer and user discovery, define success metrics (KPIs and OKRs), and measure outcomes
- Manage stakeholders across CDAO, the Global Private Bank, and partner teams; communicate trade-offs and progress
- Champion data quality, governance, privacy, and regulatory compliance throughout the product lifecycle
- Bring demonstrated, hands-on experience as a product manager who ships AI- and LLM-powered features and products, including the application of retrieval-augmented generation (RAG) and AI agents
- Use AI and LLM tooling within your own product management workflow to accelerate discovery, requirements definition, prototyping, and delivery
- Partner closely with applied AI and data science teams to operationalize models responsibly, with appropriate controls for quality, safety, privacy, and compliance
- Champion an AI-forward mindset across the portfolio, identifying where intelligent capabilities can meaningfully improve data products and the experiences built on top of them
Deliver unified data products across multiple core data domains, aligned with the data mesh strategy
Required qualifications, capabilities, and skills
- Financial services experience commensurate with a Vice President level role of 7 years, in data and analytics, wealth /private banking, related domains
- Demonstrated product management experience delivering data and/or analytics/AI products end to end
- Strong, demonstrated experience building and shipping AI- and LLM-powered products, and fluency using AI and LLM tools within the product management workflow. This is a core requirement of the role
- Familiarity with modern data platforms (Snowflake, Starburst, Databricks) and data product and data mesh concepts
- Strong analytical, communication, and stakeholder management skills, with the ability to lead through influence across engineering pods
- Bachelor's degree required
Preferred qualifications, capabilities, and skills
- Experience with regulatory and compliance data products
- Experience with GenAI/LLM application patterns, prompt engineering, AI agents, and vector search / retrieval-augmented generation (RAG)
- Familiarity with operating within a federated data mesh model
- Advanced degree a plus