• Establish and own the independent validation framework for fraud models and AI-enabled decision systems across OKX products, covering conceptual soundness, data quality, implementation, and outcomes analysis, in line with SR 26-2 and equivalent model risk frameworks.
• Assess model conceptual soundness, intended use, assumptions, and limitations.
• Personally execute end-to-end model validations as the technical expert, including independently reproducing results through hands-on data analysis and code review.
• Assess AI/ML and generative AI applications, including LLM-based and agentic systems, for robustness, reliability, explainability, and appropriate human oversight, applying strong applied AI evaluation expertise.
• Perform ongoing monitoring review and periodic revalidation to ensure sustained model performance through changing fraud patterns and business conditions.
• Provide effective challenge to model owners; communicate conclusions, limitations, and risk ratings clearly to senior management and governance forums, and track remediation through closure.
• Build and continuously mature the fraud model validation capability, standards, and workflows within MRM.

• Master’s or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, or a related discipline, or equivalent experience.
• 10+ years of quantitative, fraud risk, or model risk experience, with a recognized track record as a hands-on technical expert who personally delivers independent validations of models and decision systems.
• Excellent communication and judgment, including the ability to explain quantitative findings to senior audiences and constructively challenge model owners.
• Practical experience with statistical and machine learning methods; proficiency in Python and SQL; working knowledge of SR 11-7 or equivalent model risk and AI governance frameworks.
• Experience with AI/ML governance and controls, including explainability, fairness, robustness, ongoing monitoring, or generative and agentic AI applications in fraud operations.

• Experience establishing validation frameworks, methodologies, or capabilities in settings where they did not previously exist.
• Strong applied AI capability: hands-on experience evaluating or building ML/LLM-based systems in production, including prompt engineering, evaluation harnesses, fine-tuning assessment, or agentic AI workflows; able to run red-team style testing on AI applications.

OKX Statement: