Traded Products Business Intelligence Lead - Wholesale Credit Risk - Vice President

Bring your Expertise to JPMorganChase. As part of Risk Management and Compliance, you are at the center of keeping JPMorganChase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

As a Wholesale Credit Risk Traded Products Business Intelligence Product Lead in Risk Management and Compliance team, you will help transform credit risk business intelligence capabilities by migrating legacy infrastructure and reports to strategically sourced data and reusable analytical models. You bring broad traded products expertise to a reporting environment combining traded products and lending exposures, supplying governed data for management and regulatory reporting. You partner with end users and Technology to translate business needs into analytical requirements and governed self-service analytics. You help us deliver reusable, accurate models, reconciled migrations, consistent business definitions, and increased user self-service.

Job responsibilities:

- Own analytical requirements, priorities, and the roadmap for assigned data products supporting wholesale credit risk reporting across traded products and lending exposures
- Solicit, capture, document, and translate business requirements from end users into analytical and semantic model requirements.
- Partner with Technology to build, implement, and deploy Databricks data tables and analytical models for use in ThoughtSpot, providing domain expertise, design guidance, and business validation.
- Align strategic sourcing and delivery across Credit Risk and partner organizations, including individual lines of business, product teams, Finance, Operations, and Technology; communicate priorities, progress, risks, and dependencies to senior stakeholders.
- Lead the rationalization and prioritization of legacy reporting definitions and calculations into shared, governed analytical models for assigned data products, using agreed definitions and calculations while preserving necessary distinctions specific to each product.
- Define data quality, lineage, metadata, reconciliation, and control requirements, and work with accountable source and technology teams to resolve issues affecting analytical use cases.
- Drive governed self-service adoption in ThoughtSpot through selected prototypes, training, reusable examples, and guidance on migrating legacy reports; validate capabilities with users and enable them to create and maintain analytics using approved data and business definitions.

Required Qualifications, Capabilities, and Skills:

- 7 plus years of progressive experience working with traded products and complex financial data in credit risk, product analysis, data architecture, or a related discipline within a financial institution.
- Broad understanding across traded product families, including derivatives, securities, futures, and options, with strong expertise in how their structures, lifecycles, and exposure characteristics are represented in data, and a foundational understanding of credit risk exposure concepts needed to interpret that data accurately.
- Ability to translate complex product and credit risk questions into analytical model requirements, defining data relationships, measures, and business rules and assessing whether outputs accurately reflect the underlying business concepts.
- Ability to prioritize business and data requirements, define acceptance criteria, and partner effectively with technology teams to guide design, implementation, and validation.
- Strong proficiency in SQL and data analysis, with the ability to investigate complex datasets, validate business logic, reconcile outputs, and communicate findings clearly.
- Sound understanding of data quality, reconciliation, ownership, lineage, and controls, with the judgment to identify issues affecting the reliability of credit risk analysis.
- Exceptional communication and stakeholder management skills, with the ability to translate among credit risk, product, data, and technology audiences, influence decisions across organizational boundaries, and explain complex data concepts clearly to support learning and adoption by end users.

Preferred Qualifications, Capabilities, and Skills:

- Experience with self-service BI and design of semantic layers, including business measures, user enablement, or governed BI assets in ThoughtSpot or a comparable platform.
- Experience rationalizing legacy reporting logic and migrating analytical use cases to strategic data and BI platforms.
- Experience with Databricks or a comparable cloud data platform, data integration, Unity Catalog, or data mesh concepts.
- Experience leading a data or BI product roadmap, backlog, or delivery initiative across teams.
- Intellectual curiosity and demonstrated ability to apply tools powered by AI, including large language models, to improve analysis, prototyping, or documentation, while critically validating outputs and following information security requirements.