AI Model Risk & Governance Manager (12-month contract)

Position Summary

We are seeking a forward-looking and detail-oriented Risk Manager to join our AI Model Governance team within the Risk Analytics and Governance Department (RAGD).

This team provides second-line oversight, review, and challenge for AI/ML model risk initiatives across the Bank.

Reporting to the Senior Manager of AI Model Governance, you will play a crucial role in operationalizing the Bank’s Responsible Use of AI framework.

You will be responsible for the day-to-day execution of AI model risk assessments, ensuring that our risk taxonomy and review standards are rigorously applied.

This is a unique opportunity to gain exposure to a wide range of AI applications in a leading financial institution and contribute directly to the firm’s evolving risk management landscape.

Responsibilities

• AI Use Case Assessment & Review: Perform initial risk assessments on new AI initiatives to evaluate impact, reliance, and complexity. Ensure use cases are correctly categorized (High, Medium, Low, or Whitelisted) within the governance pipeline.
• Framework Execution & Policy Maintenance: Apply and maintain the AI Model Risk Taxonomy, ensuring all risks, from Generative AI to traditional regressions, are identified and mapped to appropriate controls. Support the Section Head in developing and operationalizing the Residual Risk Framework by identifying gaps between inherent risks and existing controls.
• Monitoring, Inventory & Compliance: Review model performance monitoring reports, identifying AI-specific issues such as data drift, model decay, and output bias, etc. Monitor local and international regulatory developments (e.g., HKMA guidance, MAS AI Risk Operationalization Handbook) and perform gap analyses to ensure internal standards remain compliant.
• Stakeholder Advisory & Support: Work closely with model developers, data scientists, and business units to provide guidance on documenting model purpose, risk tiers, and navigating the approval process.

Requirements

• Bachelor’s or master’s degree in a quantitative field (e.g., Statistics, Analytics, Data Science, Mathematics, Quantitative Finance, Risk Management or Computer Science, etc.) is preferred
• 3–5 years of experience in Model Risk Management (MRM), Model Governance, or Data Science within the financial services industry
• Understanding statistical modeling and machine learning algorithms (e.g., NLP, Tree-based models, Deep Learning) and their associated risks
• Understanding technical standards for AI evaluation, including Explainability (XAI), Fairness, and Robustness
• Proficiency in Python or R is highly preferred, including experience with data science libraries (e.g., NumPy, Pandas)
• Experience with banking governance platforms is a plus
• Understanding of HKMA’s guidance on AI and general Model Risk Management requirements (e.g., SR26-2)
• Ability to work effectively in a fast-paced environment with evolving AI regulations and limited precedents
• Excellent English written and verbal communication skills, with ability to explain technical risk findings to non-technical stakeholders and challenge the status quo constructively
• Exceptional focus on accuracy across technical documentation and risk evaluations.

A hands-on contributor who is willing to dive into the details to ensure all operational and governance requirements are met

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Applicants who are not invited for interviews within six weeks may consider their applications unsuccessful and the personal data collected will be destroyed after 1 year.