The Quantitative Model Validation Analyst role is part of the Bank’s Risk Management and Compliance organization, specifically supporting the Model Risk Management (MRM) program. This program provides governance, oversight, and control processes for identifying, measuring, monitoring, and managing model risk across the enterprise. The analyst will provide independent and effective challenge of models used for critical business, financial, and risk management decisions. The role focuses on the independent validation of macroeconomic forecasting models used in regulatory and business planning, including CCAR, CECL, capital planning, and other business-as-usual activities. The incumbent will collaborate with Model Owners and Developers to conduct risk-focused validations, challenging model assumptions, theoretical foundations, estimation techniques, variable selection, forecasting performance, sensitivity analyses, and outcome reasonableness. All validation activities must comply with regulatory guidance and the Bank’s Model Risk Management Policy and Standards. The role involves assessing model risks, limitations, uncertainties, and potential sources of forecast error, providing conclusions on model appropriateness and fitness for use. The position requires strong analytical and quantitative skills, including econometrics, time-series analysis, macroeconomic forecasting, stress testing, and statistical model performance evaluation. Independent testing, benchmarking, back-testing, and sensitivity analysis will be conducted to assess conceptual soundness, ongoing performance, and regulatory compliance. The analyst will document validation procedures, findings, and conclusions in reports and present results to stakeholders, including model owners, developers, governance committees, and executive management. Regular interaction with Risk Management, Finance, Treasury, and Business Lines is expected, as well as interfacing with regulators (OCC and Federal Reserve) and Internal Audit to discuss validation approaches, findings, model risk assessments, and remediation recommendations. Effective communication of complex quantitative concepts to both technical and non-technical audiences is essential.
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Job Type
Full-time
Career Level
Mid Level