Senior Model Validation Specialist
1 month ago
Citi is seeking a highly skilled Senior Model Validation Specialist to join our Risk Management team. As a key member of our Artificial Intelligence (AI) Review and Challenge Group, you will be responsible for performing independent review and effective challenge of all lifecycle activities of AI/ML non-model objects used in Citi.
Key Responsibilities- Provide independent review and effective challenge on the soundness and fit-for-purpose of AI/ML non-model objects used in Citi
- Manage AI/ML risk across all life-cycle activities including initial review, ongoing monitoring, and periodic reviews
- Conduct analysis and prepare detailed technical documentation reports sufficient to meet regulatory guidelines and exceed industry standards
- Identify weaknesses and limitations of AI/ML objects and inform stakeholders of their risk profile and recommend compensating controls
- Communicate results to diverse audiences such as AI/ML object owners and developers and senior management
- Manage stakeholder interactions with AI/ML object developers and owners across the review lifecycle
- Provide guidance to junior reviewers as and when necessary
- Contribute to strategic, cross-functional initiatives within the model risk management organization
- Validate NLP binary, multiple-class, and deep learning models to assess model risk and ensure compliance with regulatory standards
- Collaborate with data scientists and machine learning engineers to understand the models, their use cases, and the associated risks
- Stay updated with the latest industry trends, best practices, and regulatory requirements related to NLP and machine learning models
- Ensure the models are in line with the company's risk appetite and meet the necessary regulatory requirements
- Translate complex NLP models and their risks to non-technical stakeholders
- 8+ years' experience
- Model validation experience using NLP techniques is mandatory
- Experience/familiarity with AI/ML applications in areas such as generative AI, cybersecurity, chatbot, natural language processing, image/voice recognition, robotic process automation
- In-depth technical knowledge of generative AI, common AI/ML techniques, and strong understanding of risks associated with generative AI, AI/ML, and corresponding mitigants
- Ability to collaborate with peers and stakeholders with various backgrounds and to effectively explain technical terms to audiences with different levels of technical knowledge
- Ability to conduct independent research on cutting-edge technology about generative AI
- Self-motivated and detail-oriented
- Masters with a specialization in Statistics, Mathematics, Finance, or other quantitative discipline - data science, AI/ML, etc. preferred
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