As a Senior Product Associate in Personalization & Customer Insights Team, you are the day-to-day execution lead for the Customer Intelligence Hub. You will own feature delivery from discovery through production, manage the product backlog across engineering teams, run experiments to validate ranking models and summary quality, and partner closely with Data Scientists on model evaluation — including LLM-as-a-Judge quality scoring and contextual bandit optimization. You are responsible for translating strategy into sprint-level delivery that ships measurable customer value.
The Customer Intelligence Hub is the personalized content generation layer — it takes what we know about a customer and generates what gets said to them and about them. But generation is only the starting point. The platform also discovers new moments that matter by mining customer data and behavioral patterns, proactively surfaces intelligence triggered by customer events (not just on-demand requests), predicts which insights will resonate before they reach a customer, and continuously learns from engagement signals to get sharper over time. Every generation emits natural language for humans and structured companion data for machines. Your consumers include bankers in branches, digital mobile and web surfaces, and more.
- Partners with the Product Manager to identify new product opportunities that reflect the needs of our customers and the market through user research and discovery
- Considers and plans for upstream and downstream implications of new product features on the overall product experience
- Supports the collection of user research, journey mapping, and market analysis to inform the strategic product roadmap and provide insight on potential product features that provide value to customers
- Analyzes, tracks, and evaluates product metrics including work to time, cost, and quality targets across the product development life cycle
- Writes the requirements, epics, and user stories to support product development
- Own sprint backlog end-to-end (epics, stories, refinement) and manage delivery across multiple engineering teams.
- Lead ranking/selection and summary-quality testing (hypotheses, A/B design, measurement) with Data Science/ML partners.
- Run a data-led pipeline to mine behavior, identify “moments that matter,” and ship ranked candidate insights every sprint.
- Define triggers (events, account changes, thresholds) to push pre-computed insights to channels ahead of customer need.
- Evolve a reusable generation platform; drive production hardening, compliance, and operational excellence with platform engineering.
- Enable self-service discovery, partner with business/marketing, and track KPIs (cycle time, engagement lift, model performance, companion-data adoption, trigger coverage).
- 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
- Experience shipping ML/AI-powered features to production in close partnership with Data Scientists and Engineers
- Strong backlog management skills: JIRA epics, user stories, acceptance criteria, refinement, sprint planning, and delivery tracking
- Data literacy: ability to read model metrics, interpret experiment results (A/B tests, statistical significance), and make prioritization decisions based on data
- Experience working with Data Scientists on the model lifecycle — design, evaluation, deployment, and monitoring
- Comfort with LLM-based products: prompt engineering concepts, quality evaluation methodologies, and output governance
- Clear, structured communicator with strong written and presentation skills; ability to translate technical complexity into stakeholder-ready narratives
- Proven ability to work across technical and non-technical teams — comfortable partnering with Data Scientists on model design and with marketing or product teams on use-case adoption
- Familiarity with recommendation or ranking systems (contextual bandits, LinUCB, DLRM, embeddings)
- Experience with LLM evaluation pipelines (LLM-as-a-Judge, quality rubrics, automated scoring)
- Understanding of personalization at scale, particularly in financial services
- Experience with real-time ML serving infrastructure (Ray Serve, streaming pipelines, Flink/Kafka, or equivalent)
- Experience with API-first delivery on cloud (e.g., AWS) and coordination across multi-channel experiences (mobile, web, branch, contact center)
- Demonstrated prior experience working in a highly matrixed, complex organization
- BS or MS in Engineering, Data Science, Business, or a comparable field of study
Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the TeamSkills 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
- Experience shipping ML/AI-powered features to production in close partnership with Data Scientists and Engineers
- Strong backlog management skills: JIRA epics, user stories, acceptance criteria, refinement, sprint planning, and delivery tracking
- Data literacy: ability to read model metrics, interpret experiment results (A/B tests, statistical significance), and make prioritization decisions based on data
- Experience working with Data Scientists on the model lifecycle -- design, evaluation, deployment, and monitoring
- Comfort with LLM-based products: prompt engineering concepts, quality evaluation methodologies, and output governance
- Clear, structured communicator with strong written and presentation skills
- Proven ability to work across technical and non-technical teams
- Familiarity with recommendation or ranking systems (contextual bandits, LinUCB, DLRM, embeddings)
- Experience with LLM evaluation pipelines (LLM-as-a-Judge, quality rubrics, automated scoring)
- Understanding of personalization at scale, particularly in financial services
- Experience with real-time ML serving infrastructure (Ray Serve, streaming pipelines, Flink/Kafka, or equivalent)
- Experience with API-first delivery on cloud (e.g., AWS) and coordination across multi-channel experiences
- Demonstrated prior experience working in a highly matrixed, complex organization
- BS or MS in Engineering, Data Science, Business, or a comparable field of study
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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