AVP, Model Validation Analyst (Hybrid)

As part of the Fraud Analytics, Modeling & Intelligence organization, the Business Modeling and AI Validation Analyst (VP) manages the documentation and validation of the fraud analytics models supporting Citi’s North American and global credit card and retail bank businesses. The Fraud Model Documentation & Data Governance team is responsible for documenting, reviewing, and assessing qualitative models as part of Citi’s Model Risk Management framework. The main objectives are to ensure that qualitative models are used appropriately by the business and that model users are aware of the models’ limitations and weaknesses that should be mitigated by compensating controls. A qualitative model is a model whose output is largely or entirely dependent upon key assumptions which are primarily qualitative in nature (but may have quantitative components, e.g., models that are partially based on expert judgment or other qualitative evidence). Qualitative models are held to the same high standard as all models at Citi.

This role partners closely with Vendors, MRM, Fraud Policy, Operations and various partners to keep apprised of business and technology direction to determine potential and existing fraud impacts.

Responsibilities: Qualifications: Education:

• Develops, enhances, and publishes Model/AI Development Documentation to obtain governance approval enabling business use while managing inherit risk.
• Key partner managing Fraud Model Risk including managing stakeholder interaction with model developers, Vendors, and Model Risk Management Validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews.
• Serve as in-business POC for fielding Model Risk Management Validators effective challenges to model/AI assumptions, mathematical formulation, and implementation.
• Conduct analysis and packages it into detailed technical documentation report for validation purposes sufficient to meet regulatory guidelines and exceed industry standards.
• Manages and mitigates model risk identified via model/AI limitations and work with Model Risk Management Validators to identify/develop/execute compensating controls.
• Distill diverse and complex information from various technical sources into a comprehensive, common language documentation intended for audiences without technical or Fraud knowledge.
• Contribute/Administer a comprehensive library of technical terminology and reference materials.
• Contributes to strategic, cross-functional initiatives within the Fraud Analytics organization.
• 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:

• 3+ years relevant experience in an analytical capacity required
• Experience in a quantitative role in risk management at a financial institution with experience in either model development or validation.
• Experienced user of Microsoft Office Suite, especially Excel &Word. Knowledge of SAS, Python or R language a plus.
• Ability to formulate findings clearly and concisely in a written form and strong verbal communication skills.
• Good analytic, creative thinking, and problem-solving abilities to multitask, work well under pressure, and deliver results under tight deadlines.
• Adept and meticulous at analysis and documentation of results.
• Self-motivated and detail oriented
• Demonstrated project management and organizational skills
• Practical experience using SAS/Python or similar statistical coding software to build and test prediction models. comfortable interfacing with model developers/vendors. proficiency handling very large data sets.
• Working knowledge and understanding of a variety of model development and validation testing techniques covering risk models/AI.

Education:

• Bachelor’s/University degree, Master’s degree preferred

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Job Family Group:

Risk Management

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Job Family:

Risk Analytics, Modeling, and Validation

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Time Type:

Full time

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