Model Validation 2nd LOD Sr. Analyst

Citi • New York, NY

3d • $140,800 - $153,300 • Hybrid

About The Position

Citibank, N.A. seeks a Model Validation 2nd Line of Defense Senior Analyst for its Long Island City, New York location. The role involves managing and assessing model risk throughout the entire lifecycle of Wholesale Credit Risk models, including initial validation, ongoing performance monitoring, and periodic re-validations/annual reviews. This includes performing independent and comprehensive validation of Wholesale Credit Risk models using various methodologies for the modeling of PD, LGD, EAD, ECL, and Loan Pricing. The analyst will evaluate the completeness, accuracy, and relevance of data inputs, design and execute advanced quantitative and statistical testing, and analyze the impact of macroeconomic scenarios on the bank's credit portfolio. A key responsibility is producing detailed, transparent, and high-quality model validation reports and communicating model risk to stakeholders. A telecommuting/hybrid work schedule may be permitted.

Requirements

• Master’s degree or foreign equivalent, in Mathematics, Finance, Statistics, or related quantitative field and 1 year of work or internship experience as a Model Developer, Model Validator, Risk Analyst, Financial Analyst, Quantitative Analyst or related position involving developing or validating statistical and quantitative models for financial risk management or quantitative research.
• Alternatively, a Bachelor’s degree in the stated fields and 3 years of the specified experience.
• Developing effective challenges to model development process.
• Validating mathematical and statistical models, including Derivatives Pricing, Monte Carlo Simulation, Ordinary Least Square Regression, Time Series Analysis, Logistic Regression, or Classification, and evaluating conceptual soundness of the model and mathematical formulation.
• Assessing adequacy and relevancy to modeling data, and assessing model performance under different specifications and scenarios, and testing sensitivity of credit risk models to macroeconomic risk drivers.
• Performing data analysis and executing quantitative and statistical tests using SAS/R, including Statistical Diagnostic Test, Sensitivity Analysis, Scenario Analysis, Stress Testing, Benchmarking, Backtesting, and Impact Analysis.
• Conducting portfolio loss simulations and tests on model convergence and performance using Python and C++.
• Programming numerical and closed-form pricing models using Python and VBA.

Nice To Haves

• Wholesale Lending Operations Management.

Responsibilities

• 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.
• 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.
• Analyze the impact of various macroeconomic scenarios on the bank's 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.
• Quantify and communicate model risk associated with identified limitations, providing actionable insights for stakeholders to understand their risk profiles and develop appropriate compensating controls.

Benefits

• medical
• dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Senior