AI Personalization Product Associate - Senior Associate

Unleash your expertise in product development and optimization by leveraging user research, analyzing metrics, and collaborating across one of the world's most innovative financial organizations. As a Senior Product Associate in the 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. Job Responsibilities Collaborates 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. Owns sprint backlog end-to-end (epics, stories, refinement) and manages delivery across multiple engineering teams. Leads ranking/selection and summary-quality testing (hypotheses, A/B design, measurement) with Data Science/ML partners. Runs a data-led pipeline to mine behavior, identify moments that matter, and ship ranked candidate insights every sprint. Defines triggers (events, account changes, thresholds) to push pre-computed insights to channels ahead of customer need. Evolves a reusable generation platform; drives production hardening, compliance, and operational excellence with platform engineering. Enables self-service discovery, partners with business/marketing, and tracks KPIs (cycle time, engagement lift, model performance, companion-data adoption, trigger coverage). Required Qualifications 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. Preferred Qualifications 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. Equal Opportunity Employer / Diversity & Inclusion 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. #J-18808-Ljbffr JPMorganChase