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Data Scientist – Credit Risk - Onsite - W2 Only - Pittsburgh, PA

ServIT Consulting LLCPittsburgh, PA🇺🇸United StatesPosted Oct 19, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Pittsburgh, PA, United States
Posted
Yesterday
SQLNLPGenerative AIPython

Job Description

Work Arrangement: Onsite – Pittsburgh, PA

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.

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