AML Model Validation Role
4 weeks ago
Primary Responsibilities
- Conduct end-to-end model validation including data input analysis, framework evaluation, code review, and outcome testing (e.g., backtesting, stress testing, sensitivity analysis).
- Apply data analysis to assess input quality, transformations, and assumptions, ensuring alignment with business and regulatory expectations.
- Evaluate model design, segmentation, variable selection, and methodology appropriateness for intended use.
- Perform detailed code reviews to ensure accuracy, consistency, and correctness; collaborate with developers on fixes.
- Analyze model performance metrics, benchmark results, and ensure robust validation across in-sample and out-of-sample data.
- Identify and challenge model risks; propose mitigation strategies to improve model robustness and regulatory compliance.
Skills:
- Strong understanding of regulatory requirements, particularly those related to stress testing and capital planning: SR 11-7, OCC 2011-12.
- Experience in using statistical tools like Python and R.
- Experience using SQL to pull data from enterprise warehouse databases
Experience:
- 7+ years of experience in model development, model validation, or model implementation within the financial industry;
- Proficiency in statistical methods (e.g., linear regression, logistic regression, survival analysis, ARIMA) and programming languages (e.g., SAS, Python, R, SQL).
- Experience in model development or model validation for any of the following domains: Treasury models, PPNR models, Balance sheet forecasting models, ALM models, Valuation models, Counterparty credit risk models etc.
- Knowledge of statistical and machine learning models.
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