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You will define and oversee the strategy, governance, and enterprise-wide assurance of analytical models and AI systems. This role ensures that all models and AI solutions operate to the highest standards of quality, fairness, regulatory compliance, and operational resilience. The leader will establish and embed assurance frameworks spanning model risk management, AI safety, validation, monitoring, and responsible AI practices. They will collaborate closely with teams across Modeling, Technology, Risk, Operations, Legal, and Compliance to promote transparency and trust in AI-driven decisioning. The role also drives continuous improvement, innovation, and consistency in how models are designed, evaluated, deployed, and monitored, ensuring analytics and AI capabilities deliver meaningful business value while effectively mitigating risk.
Job Responsibility:
Define and oversee the strategy, governance, and enterprise-wide assurance of analytical models and AI systems
Ensure all models and AI solutions operate to the highest standards of quality, fairness, regulatory compliance, and operational resilience
Establish and embed assurance frameworks spanning model risk management, AI safety, validation, monitoring, and responsible AI practices
Collaborate closely with teams across Modeling, Technology, Risk, Operations, Legal, and Compliance to promote transparency and trust in AI-driven decisioning
Drive continuous improvement, innovation, and consistency in how models are designed, evaluated, deployed, and monitored
Collect, clean, analyse, and visualise data to identify potential risks, assess compliance with regulations, and provide valuable insights to auditors
Development and execution of data extraction strategies
Analysis of data to identify potential risks and control weaknesses
Provision of data-driven insights and analysis to auditors
Supporting the development and testing of audit procedures
Implementation of data management processes
Requirements:
Extensive experience leading model risk management, AI assurance, or advanced analytics governance in a regulated sector such as financial services, banking, credit, or insurance
Expertise in machine learning, statistical modeling, model validation, and AI/ML monitoring, with familiarity in emerging AI regulatory expectations
Demonstrated leadership in managing cross-functional programs, influencing senior stakeholders, and implementing enterprise-scale governance or AI assurance frameworks
Nice to have:
Experience building Responsible AI programs or integrating fairness, explainability, and transparency into machine learning development lifecycles
Thorough understanding of modern cloud data platforms, MLOps/LLMOps practices, and emerging AI and GenAI architectures
Previous oversight of hybrid teams across analytics, risk, data science, and technology, with the ability to evolve and scale organizational capabilities