Citi Group SVP Fraud Model Validation Sr Lead 

United States, Texas, San Antonio 

436988258

Responsibilities:

• Partner closely and manage interaction with model developers, vendors, and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews.
• Lead the validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation.
• Provide strategic guidance to vendors, developers and business partners on model documentation, model assumptions, data sources and interpretation of validation results.
• Conduct rigorous validation assessment for fraud model validation; develop and implement validation methodologies to assess model accuracy, robustness and effectiveness.
• Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation.
• Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies
• Identifies and compiles data sets using a variety of tools (e.g. SQL, Access) to help predict, improve, and measure the success of key business to business outcomes
• Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / algorithms and data visualization techniques
• Incumbents in this role may often be referred to as Data Scientists
• Specialization in marketing, risk, digital and AML fields possible
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 8+ years of experience
• Strong proficiency in statistical analysis and model validation techniques.
• A solid grasp of traditional and advanced modeling techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc.
• Expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc.
• Familiarity with regulatory requirements and guidelines related to risk model validation.
• Working experience in a quantitative field, Financial/Credit Card industry preferred
• Deep modeling expertise and experience with analytic techniques and tools
• Excellent analytical thinking, practical problem solving abilities, and partnership skills
• Expertise in R, Python, H2O, and SAS
• Willing to learn and can-do attitude

Education:

• Bachelors/University degree in statistics, mathematics, physics, economics, or other analytical or quantitative discipline. Master's Degree or PhD preferred.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Anticipated Posting Close Date:

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