Vice President - Wholesale Credit Risk Portfolio Analytics

VP - Wholesale Portfolio Analytics - Grading

As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks and using your expert judgment to solve real-world challenges that impact our company, customers, and communities. The Portfolio Analytics Grading team is responsible for developing and maintaining the risk grading framework for Wholesale Credit Risk clients, including corporations across all industries. The team designs, builds, and maintains grading models and methodologies, underpinned by credit knowledge and portfolio data analysis.

Job Responsibilities:

• Lead the development of credit risk grading models and frameworks for the Wholesale Credit Risk organization. This means hands on quantitative work, strategic thinking about methodology and regular exposure to senior leadership. 
• Own the end-to-end development and enhancement of risk grading frameworks, from methodology design through implementation and validation
• Build and maintain python based pipelines for managing large credit datasets, running back tests, and producing portfolio level analytics that stress test model assumptions
• Conduct deep dive analyses on portfolio segments – identifying concentration risks, migration trends, and grading inconsistencies that inform framework calibration
• Apply LLMs to synthesize unstructured data (financials, research, news) into datasets for use in development 
• Translate complex analytical findings into clear narratives for senior committees and regulators
• Partner with Technology teams, Model Risk, and Controls to build tools and workflows that operationalize new grading methodologies
• Mentor junior analysts and associates 

Required qualifications, capabilities, and skills

• 7+ years in financial analytics or Credit Risk
• Strong python skills with hands-on experience manipulating large datasets (pandas, SQL, Numpy) and building reproducible tools and analytical workflows
•  Proven ability to build or enhance quantitative models – back testing, sensitivity analysis, scenario modeling
• Experience producing executive-level communications: decks memos, committee materials
• Comfortable presenting to senior audiences and defending analytical conclusion
• Familiarity with credit risk concepts: PD, LGD