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

JPMorganChase • Plano, TX

10d

About The Position

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

Requirements

• At least 7 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 of traded product families, including derivatives, securities, futures, and options, and strong expertise in how their structures, lifecycles, and exposure characteristics are represented in data.
• Foundational understanding of credit risk exposure concepts needed to interpret traded product data accurately.
• Ability to translate complex product and credit risk questions into analytical model requirements, define data relationships, measures, and business rules, and assess whether outputs reflect the underlying business concepts.
• Ability to prioritize business and data requirements, define acceptance criteria, and partner with technology teams to guide design, implementation, and validation.
• Strong proficiency in SQL and data analysis, including investigating complex datasets, validating business logic, reconciling outputs, and communicating findings clearly.
• Sound understanding of data quality, reconciliation, ownership, lineage, and controls, with judgment to identify issues affecting the reliability of credit risk analysis.
• Exceptional communication and stakeholder management skills, including the ability to translate among credit risk, product, data, and technology audiences, influence decisions across organizational boundaries, and explain complex data concepts to support end-user learning and adoption.

Nice To Haves

• Experience with self-service BI and semantic-layer design, 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 AI-powered tools, including large language models, to improve analysis, prototyping, or documentation while critically validating outputs and following information security requirements.

Responsibilities

• Own analytical requirements, priorities, and the roadmap for assigned data products supporting wholesale credit risk reporting across traded products and lending exposures.
• Gather, capture, document, and translate end-user business requirements into analytical and semantic model requirements.
• Partner with Technology to build, implement, and deploy Databricks data tables and analytical models for ThoughtSpot, providing domain expertise, design guidance, and business validation.
• Align strategic sourcing and delivery across Credit Risk and partner organizations, including 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, using agreed definitions and calculations while preserving necessary product-specific distinctions.
• 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 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed