AML Model Validation Role - Global Bank

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.