Join a centralized data strategy team building governed analytical foundations for one of JPMC's largest service organizations, spanning hundreds of products with distinct systems, identifiers, lifecycle stages, and domain semantics. Much of this work is upstream of analytics production — focused on setting strategy for how to formalize product-level data knowledge that today exists across scattered documentation, bespoke systems, and subject matter expertise.

As a Vice President on the Commercial & Investment Bank's Global Services Data Analytics team, you will design scalable approaches for formalizing product semantics across a heterogeneous landscape, working under the direction of the Analytics Solutions Director. Your work ensures that governed, machine-navigable data foundations support consistent cross-product analysis, AI-mediated consumption, and reliable operational decision-making.

Job Responsibilities

• Systematically discover and formalize product-level data semantics — entities, identifiers, lifecycle stages, metrics, and system touchpoints — using documentation, schemas, and SME validation
• Determine where structural data integration is required versus where documented semantic alignment is sufficient, and develop reusable principles for applying that judgment
• Build reusable patterns for identifier linkage, lifecycle mapping, and metric definition that reduce onboarding effort as more products are formalized
• Embed governance in the assets: produce versioned definitions with lineage, ownership, confidence, and known limitations; enforce validation gates before release
• Partner with Data Owners, Data Stewards, and Technology teams to validate definitions and drive approvals through the governance cadence
• Use structured intake and prioritization to route demand, manage dependencies, and balance delivery with foundation-building work
• Capture unmet analytical needs as structured demand signals and partner with stakeholders to prioritize estate expansion
• Investigate product implementation systems to understand data flows across system boundaries and surface gaps invisible to current reporting
• Support platform migrations by ensuring governed assets remain accurate as source systems and warehousing platforms evolve
• Contribute to team development across a geographically distributed, actively scaling organization
  

Required Qualifications, Capabilities, and Skills

• 7+ years in data analytics, data strategy, data integration, or management consulting in complex, multi-system environments
• Demonstrated experience linking data across heterogeneous source systems with non-trivial identifier and semantic challenges
• Strong SQL proficiency across relational and cloud-native database systems
• Experience formalizing business metrics with explicit definitions, calculation logic, and documented assumptions
• Working familiarity with generative AI and LLM capabilities, including strengths, limitations, and the need for validation guardrails
• Experience producing structured data documentation (dictionaries, lineage, metadata) as a deliberate output of analytical work
• Strong communication skills and stakeholder partnership capability
  

Preferred Qualifications, Capabilities, and Skills

• Financial services or similarly complex regulated industry experience
• Experience with modern cloud data platforms, particularly Snowflake and/or AWS-based services
• Familiarity with semantic layers, data modeling, or knowledge representation methods that formalize meaning across systems
• Experience operating governance forums and approval cadences for definitions, linkages, and quality thresholds
• Experience designing reusable onboarding approaches (patterns, templates, validation protocols) intended to scale across domains
• Comfort with AI-augmented workflows where human judgment validates AI-assisted outputs before they become authoritative
• Proficiency in Python or R for data transformation, validation, or automation
• Undergraduate or graduate degree in a quantitative, technical, or information science discipline.