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# Senior Data Scientist - Credit Risk Modeling

- **Company:** ServIT Consulting LLC
- **Location:** Pittsburgh, PA, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Data Analysis, Computer Programming, Database Queries, Python (Programming Language), Machine Learning, Natural Language Processing, Backtesting, SAS (Software), Model Validation, Generative AI, Performance Monitor
- **Published:** October 20, 2026
- **Apply:** https://www.dice.com/job-detail/c6e6ce7f-6e10-45fc-aa18-28eddfb1e629

## About the Role

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., · 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.

## Description

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., · 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., 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.