
at J.P. Morgan
Bulge Bracket Investment BanksPosted 8 days ago
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**Wealth Management - Product Owner for Investments Data - Vice President (VP)** **Summary:** - **Role:** Lead end-to-end lifecycle of data products for Wealth Management, focusing on business objectives and customer needs. - **Level:** Vice President (VP) - **Experience:** 5-7 years in data product management or relevant domain - **Skills:** - Data product life cycle management - AI readiness and application for data products - Data contracts and consumer-centric delivery - Metadata/semantics literacy - AI literacy for data products - Hands-on data and analytics fluency - **Domain Expertise:** Wealth management, private banking, client-advisor model, portfolio management, risk/suitability, tax considerations As a Vice President and Wealth Management - Product Owner for Investments Data, you will oversee the end-to-end lifecycle of data products that support business objectives and customer needs. With 5-7 years of experience in data product management or a relevant domain, you will demonstrate a strong understanding of data contracts, metadata/semantics, and AI literacy to create high-quality, AI-ready data products. Your expertise in wealth management will enable you to effectively shape data products that deliver customer value and support innovation in the private banking sector.
- Compensation
- Not specified
- City
- New York City
- Country
- United States
Currency: Not specified
Full Job Description
Location: New York, NY, United States
Join our dynamic team and make a meaningful impact by delivering high-quality, AI-ready data-products that resonate with clients. You enjoy shaping the future of data-product innovation as a core leader, guiding value for customers, successful launches, and expectations.
Job Summary
As a Product Owner within the Private Bank Chief Data & Analytics Office (CDAO), you will lead the end-to-end lifecycle of data products that support business objectives and customer needs across Wealth Management. Partnering with business, data, and technology teams, you will define product vision, manage product roadmaps, and deliver high-quality, AI-ready data products that are scalable, resilient, and aligned with governance standards. You will gather stakeholder feedback, prioritize opportunities, and measure product success through key performance indicators including data quality, adoption, reliability, and business value. This role offers the opportunity to shape innovative data products that support decision-making and enhance the firm's data capabilities.
Job responsibilities
Develop a data-product strategy that delivers value to customers
Develop a product vision that delivers value to customers
Manage discovery efforts and feedback to uncover customer solutions
Integrate customer solutions into the data-product roadmap
Own and maintain a data-product backlog
Develop a data-product backlog that enables development to support the overall roadmap and value proposition
Build the framework for the products key success metrics
Track data quality, usage, cost, feature and functionality, reliability, scalability and AI-readiness
Develop data products that are AI-ready by ensuring quality metadata and taxonomy
Guide the buildout of a rich semantic and context layer for Agentic AI to discover and use data-products
Manage the data-lifecycle and governance of data-products including data classification, data usage, data retention, data lineage, data quality and controls
Required qualifications, capabilities, and skills
Demonstrate 5 years of experience or equivalent expertise in data-product management or a relevant domain area
Apply advanced knowledge of the data-product development life cycle
Apply advanced knowledge of design
Apply advanced knowledge of data analytics
Apply advanced knowledge of data-governance
Lead data-product life cycle activities including discovery
Lead ideation and strategic development
Define requirements
Manage value
Use AI tools to define requirements, shape design, and harvest and create metadata
Create Data Quality rules
Preferred qualifications, capabilities, and skills
Demonstrate prior experience working in a highly matrixed, complex organization
Apply wealth management domain expertise across the client/advisor model, accounts, brokerage, trusts, managed accounts, portfolios/holdings, transactions, performance, fees, risk/suitability, tax considerations, and reporting expectations
Apply data contracts and consumer-centric delivery including APIs/SQL/feeds, versioning, deprecations, and backward compatibility
Apply metadata/semantics literacy including glossary/definitions, conformed entities, metric governance, and lineage comprehension
Apply AI literacy for data products including RAG concepts, grounding, entitlements-aware retrieval, evaluation, and using AI to accelerate documentation and issue triage
Use hands-on data and analytics fluency including SQL basics, KPI design, experimentation/measurement, understanding of data models and entity relationships, and basics of graph-databases
Apply a data quality and control mindset, Agile delivery and execution, and risk/privacy awareness




