Product Manager — Data Management

Job Responsibilities

• Own the product roadmap, vision, execution, risk management, and performance outcomes for the platform.
• Manage the full product lifecycle by setting strategy, translating customer needs into prioritized capabilities, and continuously adapting the roadmap to deliver business outcomes.
• Coach and mentor product teams on best practices including solution generation, market research, storyboarding, prototyping, and product delivery.
• Be accountable for product performance by investing in enhancements and addressing barriers that limit adoption, usability, and operational scalability.
• Monitor market trends, conduct competitive analysis, and identify opportunities to differentiate through modern data observability, cloud-native data ecosystems, and cost intelligence practices.
• Define and drive strategic capabilities spanning data observability, cost transparency, data state tracking, usage analytics, and centralized metrics aggregation to deliver holistic data intelligence at scale.
• Lead development of core capabilities including data readiness observability, state-based lifecycle tracking, centralized alerting, cost attribution models, and AI-driven conversational experiences.
• Drive self-service intelligence experiences that enable stakeholders to proactively assess and act on data readiness, cost, and operational signals through unified dashboards and AI-driven conversational interfaces.
• Build AI-driven intuitive conversational experiences that enable users to explore data insights, ask questions in natural language, and act on intelligence through guided, interactive dialogue.
• Drive cross-platform integration by partnering with data platforms, pipeline infrastructure, and governance teams to ensure reliable metrics availability, consistent telemetry standards, and signal correlation.
• Connect data-state signals to customer, financial, and risk outcomes to drive business-impact intelligence and informed decision-making across the organization.

Required Qualifications, Capabilities, and Skills

• 10+ years of experience or equivalent expertise delivering products, projects, or technology applications
• Extensive knowledge of the product development lifecycle, technical design, and data analytics
• Ability to drive adoption of product lifecycle activities including discovery, ideation, strategic development, requirements definition, and value management
• Experience driving change and managing stakeholders across multiple functions
• Experience partnering with compliance, security, and governance stakeholders
• Executive-level product management capability within a large organization, including strong strategic thinking and crisp product communication
• Proven experience owning data observability, data intelligence, or similar cross-platform data products that aggregate signals across distributed systems
• Strong grasp of data architecture principles including APIs, streaming, batch, lineage, data state modeling, and signal correlation patterns
• Deep understanding of multi-cloud data ecosystems, including platforms such as AWS, Databricks, and Snowflake
• Fundamental understanding of AI/ML concepts including large language models, natural language processing, and conversational AI, with the ability to translate AI capabilities into user-centric product experiences
• Familiarity with design tools such as Figma and rapid prototyping techniques to effectively collaborate with design teams and iterate on product concepts

Preferred Qualifications, Capabilities, and Skills

• Advanced degree in a related field (e.g., Computer Science, Business Administration)
• Familiarity with AI/ML integration for anomaly detection, intelligent alerting, and predictive data-state analytics
• Strong stakeholder management and executive communication skills, including experience presenting to C-level audiences
• Experience designing unified platform experiences that bridge technical depth and business accessibility and with modern data observability and intelligence platforms
• Familiarity with data state concepts, event-driven architectures, and near real-time data processing frameworks
• Experience defining responsible AI practices including managing bias, ensuring explainability, and addressing hallucination risks in AI-driven product experiences
• Familiarity with prompt engineering, conversational design patterns, and feedback-loop mechanisms for continuously improving AI-powered features

About Us

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.

About the Team

The Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions -- all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.