Wealth Management - Kyc Data Product - Product Manager

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

Product Manager for KYC Data Products in Wealth Management, focusing on end-to-end strategy, delivery, and operational excellence of data capabilities for client onboarding, regulatory compliance, and risk management. The role involves defining roadmaps, data modeling, managing distribution, enforcing governance, establishing KPIs, and leading cross-team delivery. It also emphasizes establishing guardrails for AI in SDLC.

What you'd actually do

  1. Define multi-quarter vision and roadmap for KYC data products across ingestion, storage, and distribution, balancing consumer outcomes, regulatory and control needs, and platform health.
  2. Set the conceptual and logical modelling direction for KYC data (canonical concepts, boundaries, definitions, relationships) ensuring alignment between API contracts, persistence models, and distribution schemas.
  3. Own the KYC distribution product portfolio including delivery patterns, SLAs and SLOs, schema and versioning policy, deprecation approach, and consumer onboarding model.
  4. Create and enforce product contracts, data access and entitlements patterns, privacy and PII controls, retention, auditability, and change governance for KYC data flows.
  5. Establish a KPI framework for end-to-end KYC data health: freshness, completeness, duplication, reconciliation pass rates, consumer defect rates, and adoption and reuse.

Skills

Required

  • 8+ years in Product Management, Product Ownership, or Data Product leadership, including leadership of cross-functional delivery in complex environments.
  • Demonstrated ownership of end-to-end data products (ingestion and integration through persistence to distribution).
  • Strong fluency in conceptual and logical data modelling with ability to sponsor canonical models and guide schema evolution.
  • Proven track record delivering and operating batch distribution and API-based consumption models (GraphQL strongly preferred).
  • Track record establishing SLAs and SLOs, operational metrics, and reliability practices for data delivery services.
  • Strong governance orientation: privacy and PII, entitlements and access, auditability, retention, and controlled change.
  • Demonstrated ability to use and institutionalize AI-assisted SDLC practices with appropriate templates, review discipline, and quality controls

Nice to have

  • KYC domain experience including client identification, verification, due diligence, risk rating, entity resolution, and periodic review processes.
  • Familiarity with regulatory frameworks such as AML, BSA, CDD, and EDD requirements.
  • Experience modernizing from legacy feeds to curated data products including rationalization and deprecation at scale.
  • Experience with metadata, lineage, catalogue adoption, and data product discoverability.
  • Comfort with analytics and data science methods for profiling, anomaly detection, and impact sizing.
  • Experience in wealth management or related financial services.
  • Strong written and verbal communication skills with ability to influence without authority across engineering and domain leadership

What the JD emphasized

  • AI-assisted SDLC practices with appropriate human validation and control compliance
  • regulatory compliance
  • control needs
  • control compliance
  • control needs