Vice President, Product Management — Home Lending Transformation

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Consumer & Community Banking

Product Manager for Home Lending Transformation at JPMorgan Chase, focusing on advancing operating models and delivering initiatives at scale. The role involves defining product backlogs, driving innovation, leading experiments, and leveraging AI responsibly to accelerate product delivery, discovery, and decisioning within a regulated fintech environment. The goal is to improve cycle time, adoption rates, and deliver measurable results through AI-enhanced insights.

What you'd actually do

  1. Define and prioritize the product backlog to maximize customer and business value; translate strategy into clear, measurable outcomes and sequenced delivery plans at enterprise scale, with a focus on reducing cycle time.
  2. Own delivery velocity and quality; proactively remove blockers, align stakeholders for fast decision-making, and ensure on-time, high-quality releases. Use lightweight decision frameworks and fast feedback loops to maintain momentum.
  3. Drive innovation and act as a key change agent: champion new ideas, challenge legacy processes, and lead cross-functional initiatives that transform Home Lending. Identify and deliver opportunities to create organizational value by leveraging technology, data, and customer insights to reimagine products, accelerate outcomes, and foster continuous improvement.
  4. Lead discovery and usability testing; run rapid experiments (Minimum Viable Products/A‑B tests) to validate assumptions and iterate based on quantified learning, including judicious use of AI‑driven insights where appropriate and compliant.
  5. Instrument features, analyze product performance, and publish outcome dashboards per sprint/release to drive data-driven decisions and return on investment; apply AI/ML where it enhances signal detection, forecasting, or prioritization, using firm-approved tools and guidelines.

Skills

Required

  • 3+ years of Product Owner/Product Manager experience with proven, end‑to‑end ownership delivering material customer and business outcomes; clear evidence of compressing cycle time on complex products
  • Advanced product analytics capability; uses data to set targets, instrument features, and manage to outcomes; familiarity with AI/ML concepts and firm‑approved tools to responsibly enhance discovery, prioritization, and customer experiences
  • 3+ years of hands‑on with JIRA/JIRA Align for flow management and expertise leading agile delivery (Scrum/Kanban) with measurable improvements to throughput and quality
  • Applied UX and solution design experience; proficiency with Figma and process‑mapping tools to rapidly frame problems and prototype solutions with engineering/design partners
  • Strong collaboration and communication skills to align engineering, design, and business partners; communicates priorities and progress crisply to maintain pace and technical acumen to engage on trade‑offs and architecture for scalable, resilient solutions
  • Market and competitive analysis experience to identify differentiation opportunities and inform the roadmap with evidence‑based insights
  • Bachelor’s degree in Business, Computer Science, Engineering or equivalent practical experience

What the JD emphasized

  • advancing Consumer and Community Banking (CCB) product operating models
  • mobilizing product teams to deliver initiatives at scale
  • accelerating idea‑to‑impact
  • elevating quality and speed
  • reducing cycle time
  • Use lightweight decision frameworks and fast feedback loops to maintain momentum.
  • leverage technology, data, and customer insights to reimagine products
  • run rapid experiments (Minimum Viable Products/A‑B tests)
  • quantified learning
  • Instrument features, analyze product performance, and publish outcome dashboards per sprint/release
  • data-driven decisions and return on investment
  • firm-approved AI/ML and analytics
  • adhering to governance and applying human judgment
  • reduce lead time from idea to production by 30%
  • increase adoption and completion rates by 25–50%
  • deliver high-impact experiments with measurable results
  • demonstrating how AI accelerated insights and value