VP, Personalization & Customer Insights Product

JPMorgan Chase; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorgan Chase is seeking an experienced Product Manager to lead personalization and customer insights initiatives across mobile, web, contact center, and branches. You will drive data discovery, analytics, and end-to-end product lifecycle from discovery to launch, while collaborating with data science, channel teams, and business stakeholders to prioritize opportunities.

You will translate research into roadmaps, design ML/LLM-based recommendations, run experiments, and ensure scalable,

Qualifications

• 8+ years in product management, data analytics, or a related field.
• Strong understanding of product development lifecycle and data analytics.

Responsibilities

• Develops a product strategy and vision delivering customer value.
• Manages discovery and market research to uncover solutions and integrate into roadmap.
• Lead discovery efforts with data sources and translate findings into roadmaps.
• Builds frameworks and tracks KPIs like cost, features, reliability.
• Translate user research into epics, stories, and acceptance criteria; manage backlog across discovery, launch, and improvement.
• Collaborate with Data Owners and stakeholders for data discovery and ML/LLM solutions.
• Champion data governance, lineage, quality, and explainability across AI-driven decisions.
• Uphold responsible AI and data practices with risk, privacy, and compliance teams.

Skills

Product management

Data analytics

Stakeholder management

SQL

AI/ML concepts

Tools

SQL

Data modeling

Job description

JPMorgan Chase is seeking an experienced Product Manager to lead personalization and customer insights initiatives across mobile, web, contact center, and branches. You will drive data discovery, analytics, and end-to-end product lifecycle from discovery to launch, while collaborating with data science, channel teams, and business stakeholders to prioritize opportunities.

You will translate research into roadmaps, design ML/LLM-based recommendations, run experiments, and ensure scalable,