Senior Product Associate, Data and Analytics-payments

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Commercial & Investment Bank

Product Associate for an analytics product that enables corporate treasury teams to access cash flows, produce AI-driven forecasts, and reduce manual processes. The role involves managing the product backlog, coordinating agile teams, collaborating with data scientists and designers, and driving feature testing. Experience with enterprise SaaS, fintech, or data/analytics platforms is required, along with strong collaboration skills with data scientists and experience in end-to-end feature testing.

What you'd actually do

  1. Own and manage the product backlog end-to-end: write well-formed user stories, define acceptance criteria, prioritize features using value/effort frameworks
  2. Coordinate daily stand-ups, sprint planning, backlog refinement, and retrospectives; drive agile ceremonies with discipline and pace across a distributed team
  3. Serve as the translation layer between client-facing colleagues and the engineering/data science teams
  4. Drive end-to-end feature testing: define test cases, coordinate UAT with stakeholders, document defects, and manage resolution before release
  5. Collaborate with UX/product designers on wireframes, prototypes, and usability reviews; represent the voice of the corporate treasurer in design decisions

Skills

Required

  • 3+ years of experience in product management for enterprise SaaS, fintech, or data/analytics platforms
  • Demonstrated experience running agile delivery teams using Kanban and/or Scrum methodologies; hands-on proficiency with Jira for backlog management, sprint tracking, and reporting
  • Proven ability to manage engineers - backend, frontend, or full-stack - across time zones, with strong command of engineering workflows, release management, and dependency mapping
  • Experience ingesting, synthesizing, and operationalizing client/user feedback into clearly defined product requirements
  • Strong collaboration track record with data scientists: ability to understand model inputs/outputs, define success metrics for ML features, and pressure-test model behavior with structured test cases
  • Experience in end-to-end feature testing including writing test plans, coordinating UAT, managing defect lifecycles, and owning quality gates pre-release
  • Strong written and verbal communication skills with the ability to produce tight, executive-ready product briefs and equally able to whiteboard a data flow with engineers
  • Bachelor's degree in a quantitative, technical, or business discipline

Nice to have

  • Domain knowledge in treasury management, cash flow forecasting, payments, or liquidity management; familiarity with how corporate treasury teams operate (accounts payable/receivable cycles, multi-bank cash positioning, FX exposure management)
  • Experience with or exposure to ERP and/or TMS platforms (SAP, Oracle, Kyriba, GTreasury, ION)
  • Exposure to regulatory and compliance constraints that govern data products in banking (data residency, model risk management, client data usage policies)

What the JD emphasized

  • AI-driven forecasts
  • data scientists
  • ML features
  • model behavior
  • end-to-end feature testing

Other signals

  • AI-driven forecasts
  • data scientists
  • ML features
  • model behavior