Personalization - Product, Senior Associate

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

Product role focused on leading the strategy and execution of ML-powered personalization and next-best-action capabilities, including agentic solutions, across various channels. The role involves translating research into roadmaps, collaborating with data science and ML engineering, running experiments, and operationalizing model lifecycle infrastructure within a regulated financial environment.

What you'd actually do

  1. Lead the strategy and execution of machine learning–powered personalization and next-best-action capabilities across mobile, web, contact center, branch, and marketing.
  2. Translate research and analytics into clear roadmaps, partner with data science, machine learning engineering, channel teams, and business stakeholders to prioritize opportunities, design and iterate recommendation, next-best-action, and agentic solutions, run experiments to validate impact, and operationalize scalable, reliable model lifecycle infrastructure—while upholding privacy, consent, and fairness standards.
  3. Partner with Channel/Interface teams to define how assistant memory and context are used, and help align on contracts, service levels, and guardrails for safe, reliable experiences
  4. Support machine learning–powered personalization and next-best-action initiatives by helping frame hypotheses, document use cases, and assist with experiment design and impact measurement
  5. Coordinate with data scientists and engineers across design, training, evaluation, deployment, and monitoring to ensure requirements are clear and delivery milestones are met.

Skills

Required

  • 3+ years of experience or equivalent expertise in product management or a relevant domain area
  • Proficient knowledge of the product development life cycle
  • Experience in product life cycle activities including discovery and requirements definition
  • Developing knowledge of data analytics and data literacy
  • Deliver customer-facing artificial intelligence products with data science and engineering teams across the model lifecycle
  • Build data products for agentic assistants (memory, context, signals) and integrate with channel experience teams
  • Deliver personalization and next-best-action for marketing/servicing using experiments and outcome measurement
  • Execute core product practices: discovery, requirements, and backlog management in Jira
  • Use research and metrics to drive roadmaps and deliver on time, cost, and quality
  • Collaborate and influence across product, design, engineering, and business stakeholders
  • Support application programming interface–first cloud delivery across mobile, web, contact center, branch, and marketing channels

Nice to have

  • Experience supporting personalization and decisioning products (recommendations/next-best-action) with hands-on experiment design and measurement
  • Familiarity with agentic assistant patterns (memory, context, signals) and data products enabling multi-channel customer experiences
  • Working knowledge of application programming interface–first, event-driven architectures on cloud platforms and production monitoring fundamentals
  • Understanding of responsible data and model practices (privacy, consent, fairness) in regulated environments

What the JD emphasized

  • machine learning–powered personalization
  • next-best-action
  • agentic solutions
  • model lifecycle infrastructure
  • privacy, consent, and fairness standards
  • assistant memory and context
  • guardrails for safe, reliable experiences
  • experiment design and impact measurement
  • responsible data practices with risk, privacy, and compliance partners (consent, fairness)

Other signals

  • machine learning
  • personalization
  • next-best-action
  • agentic solutions
  • model lifecycle