Personalization Product Manager - Vice President

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Consumer & Community Banking

Product Manager (VP level) at JPMorgan Chase focused on Personalization and Customer Insights. The role involves leading the end-to-end product lifecycle for AI/ML-driven personalization features, including customer journeys, next-best-action capabilities, and agentic solutions. Responsibilities include data discovery, translating research into roadmaps, collaborating with data science and ML engineering, and ensuring responsible AI practices in a regulated fintech environment.

What you'd actually do

  1. Develops a product strategy and product vision that delivers value to customers
  2. Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap
  3. Lead discovery efforts, conducting research with data sources and translating findings into well-defined roadmaps.
  4. Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability
  5. Define and own the strategy and roadmap for operating‑memory data products: what customer signals are needed, how they are represented, governed, and retrieved safely, and how they are delivered to the agent and domain agents at the right time

Skills

Required

  • product management
  • data analytics
  • product development life cycle
  • large-scale structured query language
  • event-based data
  • streaming concepts
  • dimensional modeling
  • operational data design
  • data governance
  • lineage
  • quality
  • controls
  • audit requirements
  • stakeholder management
  • communication skills

Nice to have

  • AI-driven or agentic product experiences
  • personalization engines
  • Data Analytics
  • building trusted data foundations

What the JD emphasized

  • responsible AI
  • data governance
  • privacy, consent, and fairness
  • regulated environment

Other signals

  • AI/ML product development
  • LLM/ML-based solutions
  • agentic solutions
  • model lifecycle infrastructure
  • responsible AI