Wholesale Credit Risk Quant: PD/LGD/EAD Modeling

JP Morgan Chase; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorganChase is seeking an Associate in Wholesale Credit Risk Quantitative Research to support the development and maintenance of credit risk models used in firmwide stress testing and loss forecasting frameworks, including CCAR, CECL, and IFRS 9.

The role involves working with large-scale datasets and collaborating across governance, technology, data, finance, and business stakeholders to deliver production-ready solutions.

Qualifications

• Master’s or Ph.D. in a quantitative discipline (Statistics, Econometrics, Economics, Math, Engineering, CS, Finance, Physics)
• 1+ years of relevant experience
• Strong foundation in statistical/econometric modeling (GLMs, logistic regression, time-series forecasting; clustering, decision trees)
• Experience working with large datasets (panel/time-series) and strong data analysis skills
• Hands-on Python programming
• Strong problem-solving, communication, and ability to manage multiple workstreams
• Experience producing technical documentation (governance/review)

Responsibilities

• Perform basic credit risk modeling at single-obligor and portfolio levels
• Support PD forecasting and rating migration model development
• Analyze large financial/credit/macro datasets (panel/time-series) with data cleaning and feature construction
• Perform model testing, monitoring, diagnostics, and validation support analyses
• Partner with technology teams to maintain model libraries following standards
• Prepare technical documentation for governance and regulatory reviews
• Apply interpretable AI/ML methods with strong controls and explainability

Skills

Statistical modeling

Problem solving

Communication

Project management

Education

Master’s/PhD in quantitative discipline

Tools

Python

Job description

JPMorganChase is seeking an Associate in Wholesale Credit Risk Quantitative Research to support the development and maintenance of credit risk models used in firmwide stress testing and loss forecasting frameworks, including CCAR, CECL, and IFRS 9.

The role involves working with large-scale datasets and collaborating across governance, technology, data, finance, and business stakeholders to deliver production-ready solutions.