Senior Data Scientist – Credit Risk Modeling
Pittsburgh, PA – Onsite | Banking / Financial Services | Senior Level
Position Overview
We are seeking an experienced Senior Data Scientist / Credit Risk Model Developer for a leading banking client in Pittsburgh, PA. This is a specialized quantitative modeling position requiring strong experience developing and implementing credit risk models within a regulated banking environment. The ideal candidate will combine advanced statistical modeling expertise with a strong understanding of credit risk, model governance, validation, and regulatory requirements.
This is not a general Data Science or AI/ML role. Candidates should have direct experience developing models used for credit risk assessment, portfolio risk management, lending, or financial risk management.
Key Responsibilities
· Design, develop, enhance, and implement statistical and quantitative credit risk models.
· Develop and support models involving Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and other credit-risk measures.
· Perform model development activities including data analysis, segmentation, variable selection, calibration, testing, back-testing, and performance monitoring.
· Support CECL, CCAR, stress testing, credit loss, allowance, and/or portfolio risk modeling initiatives as applicable.
· Analyze large and complex banking, lending, customer, and credit datasets.
· Apply statistical and machine-learning techniques appropriately within established banking risk-management frameworks.
· Conduct model performance analysis, sensitivity testing, benchmarking, and ongoing model monitoring.
· Prepare comprehensive model development and methodology documentation.
· Partner with Credit Risk, Model Risk Management, Independent Model Validation, Finance, Data, and Technology teams.
· Address model-validation findings and provide quantitative support for modeling assumptions and methodology.
· Ensure models and supporting documentation meet internal governance standards and applicable regulatory expectations.
Required Qualifications
· Strong hands-on experience in Credit Risk Model Development within banking or financial services.
· Strong understanding of credit-risk concepts including PD, LGD, expected credit loss, and portfolio risk.
· Experience developing, calibrating, validating, back-testing, and monitoring quantitative models.
· Strong knowledge of statistical modeling techniques including regression, classification, segmentation, forecasting, and model-performance measurement.
· Experience with Model Risk Management, Model Validation, model governance, and regulatory documentation.
· Strong programming skills using Python, SAS and/or R.
· Strong SQL skills and experience analyzing large financial datasets.
· Ability to translate complex quantitative results into clear business and risk-management conclusions.
· Strong written communication and technical documentation skills.
· Experience working in highly controlled and regulated financial environments.
Preferred Qualifications
· Experience with CECL, CCAR and/or regulatory stress testing.
· Experience developing commercial or consumer credit-risk models.
· Familiarity with banking lending products and credit lifecycle processes.
· Experience working directly with independent model-validation, audit, compliance, or regulatory teams.
· Advanced degree in Statistics, Mathematics, Economics, Econometrics, Data Science, Financial Engineering, or another quantitative discipline.
Candidate Profile
The successful candidate should be a true risk-model developer, rather than a general Data Scientist focused primarily on AI, Generative AI, NLP, reporting, or analytics. Direct experience building and supporting credit-risk models within a banking environment is essential.
Work Arrangement: Onsite – Pittsburgh, PA
