Model Validation 2nd LOD Sr. Analyst - C12

Model Validation 2nd LOD Sr. Analyst - C12

Citibank, N.A. seeks a Model Validation 2nd LOD Senior Analyst for its Tampa, Florida location.

Duties:
Manage and assess model risk throughout the entire lifecycle of Wholesale Credit Risk models, including initial validation, ongoing performance monitoring, and periodic re-validations/annual reviews. Perform independent and comprehensive validation of Wholesale Credit Risk models, including, but not limited to, those utilizing methodologies such as statistical, numerical, or mathematical approaches for the modeling of PD, LGD, EAD, ECL, and Loan Pricing.

Evaluate the completeness, accuracy, and relevance of data inputs used in Wholesale Credit Risk models, including their impact on model outputs and overall performance, with particular attention to data specific to ECL and Loan Pricing projection. Conduct rigorous assessment and effective challenge of model design, underlying assumptions, conceptual soundness, and mathematical formulations, ensuring alignment with industry best practices and regulatory requirements for all relevant model types.

Design and execute advanced quantitative and statistical testing, including scenario analysis, stress testing, and backtesting, using programming languages such as Python, R, or SAS, to evaluate model integrity, stability, and predictive performance. Review model performance against macroeconomic conditions based on drivers across different industries, regions, and product types. Analyze the impact of various macroeconomic scenarios on the credit portfolio, particularly when validating models used for stress testing, capital adequacy, and ECL estimation.

Produce detailed, transparent, and high-quality model validation reports that clearly articulate findings, limitations, and recommendations, adhering strictly to Model Risk Management Policy and Execution Manuals. Serve as a subject matter expert, effectively representing the bank in discussions with regulatory authorities, internal audit, and external auditors regarding Wholesale Credit Risk model validation findings and model risk management practices, and present complex validation outcomes and model risk assessments to senior management and supervisory bodies.

Quantify and communicate model risk associated with identified limitations, providing actionable insights for stakeholders to understand their risk profiles and develop appropriate compensating controls. Collaborate with model development teams, business lines, and other stakeholders to facilitate a robust model lifecycle and ensure effective communication of validation results, while contributing to the continuous enhancement of the bank's Model Risk Management framework and participating in strategic, cross-functional initiatives within the model risk organization.

A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with Citi policies and protocols.

Requirements:
Requires a Master's degree or foreign equivalent in Mathematical Finance, Mathematics, Statistics, or related quantitative field 2 years of experience as a Model Developer, Model Validator, Model/Analysis/Validation Senior Analyst, or Quantitative Analyst performing financial model validation and performance testing for a global financial services institution. Alternatively, employer will accept a Bachelor's degree in the above fields and 5 years of progressively responsible experience in the above positions.

Full span of experience must include:
Validating mathematical and statistical models, including Derivatives Pricing, Monte Carlo Simulation, Ordinary Least Square Regression, Time Series Analysis, Logistic Regression, and Classification;
Assessing data inputs used in model development and validation, ensuring the quality and appropriateness of data;
Designing and executing Statistical Diagnostic Tests, Scenario Analysis, Stress Testing, Benchmarking, Backtesting, and comprehensive sensitivity analysis on wholesale credit risk models to key macroeconomic risk drivers;
Conducting portfolio loss simulations and tests on model convergence and performance using Python/C++;
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