Data Science Lead - Vice President

JPMorganChase • Jersey City, NJ

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About The Position

Shape the future of data science while crafting solutions that enhance and optimize customer experiences. Lead end-to-end processes, manage dependencies, and liaise with stakeholders as part of a team at the forefront of innovation. As a Data Science Vice President within the Commercial and Investment Bank Technology team, you are an integral part of a team that works to develop high-quality architecture solutions for various software applications and platforms products. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains.

Requirements

• Advanced degree (master’s or higher) in Computer Science, Data Science, Engineering, Applied Mathematics, Statistics, or a related quantitative discipline.
• 5+ years of experience developing and deploying Data Science solutions.
• 3+ years of experience as a Technical Program Manager or equivalent role delivering data platform, analytics, or metrics infrastructure programs in a regulated financial services environment.
• Hands-on proficiency with modern data stack components—dimensional modeling, dbt or equivalent transformation frameworks, and columnar/lakehouse storage—sufficient to independently evaluate technical trade-offs.
• Demonstrated ability to define and socialize a product vision, build consensus with skeptical domain experts, and translate ambiguous business requirements into actionable engineering specifications.
• Experience operating in lean/agile environments with rapid iteration cycles; comfort with ambiguity and willingness to own outcomes end-to-end without a fully staffed team.
• Strong data literacy: ability to read and reason about SQL, understand metric grain and aggregation correctness, and identify when a proposed definition will produce inconsistent results across contexts.

Nice To Haves

• Practical experience with semantic layer technologies (dbt MetricFlow, LookML, AtScale, or equivalent) and an appreciation for the governance challenges of a shared metrics store across competing business domains.
• Background in payments, card processing, or transaction banking
• Exposure to federated query engines, data observability tooling, or real-time monitoring applications

Responsibilities

• Engage with stakeholders to identify and define business needs and opportunities, and design technical solutions to address them.
• Partner with product managers, engineers, and functional experts across the end-to-end AI/ML lifecycle—conception, validation, scaling, production delivery, and performance monitoring.
• Own end-to-end delivery of the Metrics Store (MORPHEUS) program—defining roadmap, managing dependencies, and tracking milestones across data engineering, semantic layer, and BI integration workstreams.
• Facilitate cross-functional workshops with domain experts in Payments Liquidity, Merchant Services, and Embedded Banking to elicit, validate, and govern metric definitions.
• Drive adoption of the unified semantic layer by crafting clear value narratives for managing directors and operational stakeholders, and removing organizational blockers to SME participation.
• Apply lean and agile delivery practices—running structured sprint ceremonies, maintaining a prioritized backlog, and iterating rapidly on platform capabilities based on stakeholder feedback.
• Develop deep subject-matter expertise in Payments processing, transaction lifecycle, and operational SLOs to translate business intent into precise metric specifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees