Senior Validator - Artificial Intelligence Non-Model Risk Review Assistant Vice President: Citi
    
        Oct 4, 2025   |  
        Location: Wilmington, Delaware, US (Hybrid).   |  
        Deadline: Oct 9, 2025    
            Experience: Senior
    
            Continent: North America
    
            Salary: $96,400.00 - $144,600.00
    
    
        This role is within Citi's Model Risk Management (MRM) on the AI Non-Model Risk Review Team. As a Senior Validator, you will be responsible for managing model risk associated with AI Non-Model Objects across Citiβs various lines of business, with a strong emphasis on Generative AI. This is an individual contributor role that involves validating Generative AI models and developing MRM's Generative AI Use Cases, offering a unique opportunity to shape the future of AI risk management within the company.
Responsibilities
Manage a portfolio of Generative AI and Natural Language Processing (NLP) models, performing model validations, annual reviews, and ongoing monitoring.
Evaluate the technical and functional aspects of Generative AI and NLP models, including their assumptions, mathematical formulation, and performance.
Conduct in-depth reviews of model development documentation, execute validation tests, and prepare comprehensive validation reports.
Research emerging techniques in Generative AI and NLP to keep the team at the forefront of innovation and develop standardized validation guidelines.
Present validation findings and recommendations to senior management and other stakeholders.
Collaborate with cross-functional teams to develop and implement Generative AI solutions.
Requirements
Experience:
Experience in AI/ML model development, validation, or implementation, with a strong focus on Natural Language Processing (NLP).
Hands-on experience with Generative AI models, including development, implementation, Retrieval-Augmented Generation (RAG), and prompt engineering, is highly desirable.
Advanced programming skills in Python, with proficiency in data analysis and visualization.
A deep understanding of model risk management frameworks and regulatory requirements.
Strong communication and project management skills.
Education:
A Masterβs or Ph.D. degree in a quantitative field such as Data Science, Statistics, Mathematics, Finance, or Computer Science is required.    
    
    
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