Quantitative Researcher: Wholesale Credit Risk & PD/LGD/EAD

JPMorgan Chase; Plano (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

JPMorganChase, a leading global financial services firm, seeks an Associate in Wholesale Credit Risk Quantitative Research to develop and maintain credit risk models used in firmwide stress testing and loss forecasting, including CCAR, CECL, and IFRS 9.

You will work with large-scale financial datasets and partner with governance, technology, data, finance, and lines of business to deliver production-ready solutions with interpretable AI/ML and strong controls.

Qualifications

• Master's or PhD in a quantitative field (Statistics, Econometrics, Economics, Math, Engineering, CS, Finance, Physics).
• 1+ year of relevant experience.
• Strong foundation in statistical/econometric modeling (GLMs, logistic regression, time-series forecasting).
• Experience working with large datasets (panel/time-series) and data analysis.
• Hands-on Python programming.
• Strong problem-solving, communication, and ability to manage multiple workstreams.
• Experience producing technical documentation for governance and review.

Responsibilities

• Perform basic credit risk modeling at single-obligor and portfolio levels.
• Support research, development, and enhancement of PD forecasting and rating migration models.
• Analyze large financial/credit/macro datasets, including cleaning and feature construction.
• Perform model testing, diagnostics, and validation support analyses.
• Partner with technology teams to maintain model libraries per standards.
• Prepare clear technical documentation for governance and regulatory reviews.
• Apply interpretable AI/ML methods with strong controls and explainability.

Skills

Python programming

Statistical modeling

Time-series forecasting

Data analysis

Communication

Education

Master's or Ph.D. in quantitative discipline

Job description

JPMorganChase, a leading global financial services firm, seeks an Associate in Wholesale Credit Risk Quantitative Research to develop and maintain credit risk models used in firmwide stress testing and loss forecasting, including CCAR, CECL, and IFRS 9.

You will work with large-scale financial datasets and partner with governance, technology, data, finance, and lines of business to deliver production-ready solutions with interpretable AI/ML and strong controls.