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

What you'll do

• Own the analytical requirements, priorities, and roadmap for data products supporting wholesale credit risk reporting.
• Translate business requirements from end users into analytical and semantic model requirements.
• Partner with Technology to build and deploy Databricks data tables and analytical models for ThoughtSpot.
• Rationalize legacy reporting definitions into shared, governed analytical models for assigned data products.
• Define data quality, lineage, metadata, and control requirements to resolve issues affecting analytical use cases.
• Drive governed self-service adoption in ThoughtSpot through prototypes, training, and guidance on migrating legacy reports.
• Align strategic sourcing and delivery across various internal organizations and communicate progress to senior stakeholders.

What we're looking for

• 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.
• Broad understanding of traded product families including derivatives, securities, futures, and options, including their structures, lifecycles, and exposure characteristics.
• Foundational understanding of credit risk exposure concepts to accurately interpret data.
• Ability to translate complex product and credit risk questions into analytical model requirements, defining data relationships, measures, and business rules.
• Ability to prioritize business and data requirements, define acceptance criteria, and partner with technology teams to guide design and validation.
• Strong proficiency in SQL and data analysis to investigate complex datasets, validate business logic, and reconcile outputs.
• Sound understanding of data quality, reconciliation, ownership, lineage, and controls.
• Exceptional communication and stakeholder management skills to translate complex data concepts across credit risk, product, data, and technology audiences.
• Experience with self-service BI and design of semantic layers in ThoughtSpot or a comparable platform (preferred).
• Experience rationalizing legacy reporting logic and migrating analytical use cases to strategic data and BI platforms (preferred).
• Experience with Databricks, Unity Catalog, or data mesh concepts (preferred).
• Experience leading a data or BI product roadmap, backlog, or delivery initiative across teams (preferred).
• Ability to apply tools powered by AI, including large language models, to improve analysis or prototyping (preferred).