Quantitative Research - Wholesale Credit Risk - Associate
About The Position
As an Associate in Wholesale Credit Risk Quantitative Research at JPMorganChase, you will support the development and maintenance of credit risk models used in firmwide stress testing and loss forecasting frameworks, including CCAR, CECL, and IFRS 9. You will work with large-scale financial and macroeconomic datasets and collaborate with model risk governance and review, technology, data, finance, and lines of business stakeholders to deliver well-controlled, production-ready solutions. The position requires experience in quantitative modeling, preferably in wholesale credit risk models such as probability of default (PD), loss given default (LGD), and exposure at default (EAD). JPMorganChase is a global financial services firm whose businesses include investment banking, consumer and small business banking, commercial banking, financial transaction processing, and asset management. Its Commercial & Investment Bank serves corporations, governments, and institutions in more than 100 countries.
Requirements
- Master’s or Ph.D. in a quantitative discipline such as Statistics, Econometrics, Economics, Mathematics, Engineering, Computer Science, Finance, or Physics.
- At least 1 year of relevant experience.
- Strong foundation in statistical or econometric modeling, such as GLMs, logistic regression, time-series forecasting, clustering, or decision trees.
- Experience working with large datasets, especially panel or time-series data, and strong data analysis skills.
- Hands-on Python programming experience.
- Strong problem-solving and communication skills, with the ability to manage multiple workstreams.
- Experience producing technical documentation, including documentation for governance or review.
Nice To Haves
- Exposure to wholesale credit risk and/or credit risk modeling; PD, LGD, or EAD modeling is strongly preferred.
- Experience with CCAR, CECL, and/or IFRS 9 modeling environments.
- Knowledge of numerical methods such as optimization or root finding, and/or large-scale computation such as Monte Carlo, multi-core, or HPC.
- Experience using AI/ML methods in risk contexts with attention to interpretability and governance.
Responsibilities
- Perform basic credit risk modeling at both the single-obligor and portfolio levels.
- Support research, development, and ongoing enhancement of PD forecasting and rating migration models.
- Analyze large financial, credit, and macroeconomic panel and time-series datasets, including data cleaning and feature construction.
- Perform model testing, monitoring, diagnostics, and validation support analyses.
- Partner with technology teams to maintain model libraries according to the organization’s software development standards.
- Prepare clear technical documentation and support internal governance and regulatory review requests.
- Apply appropriate, interpretable AI/ML methods where suitable while maintaining strong controls and explainability.
Benefits
- Competitive total rewards package, with base salary determined by role, experience, skill set, and location.
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
- Comprehensive health care coverage.
- On-site health and wellness centers.
- Retirement savings plan.
- Backup childcare.
- Tuition reimbursement.
- Mental health support.
- Financial coaching.
- Other benefits and programs based on eligibility.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
