Wealth Management - Data Strategy & Architecture, Client Acquisition Lifecycle, Analytics, and Applied AI Director

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Asset & Wealth Management

This role focuses on defining and evolving data strategy and target-state architecture for client acquisition, analytics, and applied AI within a Global Private Bank. The Director will partner with business and technology leaders to deliver scalable data models, enable strategic data provisioning, and drive lifecycle-aware solutions supporting operational, analytical, and regulatory needs. A key responsibility is developing cross-domain, consumer-focused data products for analytics and agentic AI, establishing scalable modeling patterns, and managing a team of data architects.

What you'd actually do

  1. Own and align CALM data strategy and architecture across KYC, onboarding, CRM, and related capabilities
  2. Define and maintain domain structures and core data concepts with clear, implementable relationships
  3. Guide data product delivery for data continuity and interoperability across GPB and adjacent verticals
  4. Design reusable, lifecycle-aware datasets for operational, analytical, risk, and regulatory use cases
  5. Develop cross-domain, consumer-focused data products for analytics and agentic AI

Skills

Required

  • 8 years of proven ability to create data strategy, design data architecture, and/or drive data transformation through change initiatives in complex organizations
  • Demonstrated ability to partner or consult with business product managers, process owners, and consumption stakeholders across front office, analytics, risk, regulatory, and controls
  • Knowledge of the financial services client lifecycle (CRM, Party Master, Account Master, KYC, Onboarding, Relationship Maintenance)
  • Track record working with technology teams to deliver data mesh capabilities, data products, semantic layers, and/or analytics
  • People leadership capability, including direct management experience
  • Expertise in domain modeling and scalable, lifecycle-aware data modeling, including conceptual and logical modeling, semantic consistency, and change-tolerant patterns

Nice to have

  • Hands-on innovation using AI to improve product delivery, operations, and/or controls
  • Familiarity with party and account data management within financial services
  • Ability to translate business outcomes and requirements into clear, implementable architecture and semantic designs
  • Strong delivery orientation, including the ability to define roadmaps at the dataset and data product levels

What the JD emphasized

  • applied AI
  • agentic AI

Other signals

  • applied AI
  • agentic AI
  • data products for analytics and agentic AI
  • scalable modeling patterns
  • semantic layer design