Responsibilities :
- Determine and propose the risk-based scope of Audits covering AI and ML models.
- Engage with business partners within various lines of business and functions to identify and assess the risks and controls effectiveness relating to AI and ML models.
- Lead and contribute to Audits covering AI and ML models and produce high-quality audit reports.
- Identify and raise audit findings, if applicable, articulating the results and impact of audit fieldwork, both verbally and in writing to the business.
- Assist senior leadership of the model audit group to execute and report on business monitoring.
- Mentor and coach junior team members in the Model Risk Audit group.
- Provide quantitative modelling consultation to other audit teams and engage with business partners in ensuring effective coverage of the control environment for AI and ML models.
- Strong model development or model validation experience (5+ years) with Artificial Intelligence or Machine Learning models e.g., Natural Language Processing, Neural Networks, Deep Learning, Tree / Ensemble approaches, and Reinforcement Learning.
- Strong understanding of the implications and concepts of AI and ML model explainability, transparency and model bias.
- Knowledge of relevant regulatory requirements within model risk management such as SR11-7.
- Ability to manage and deliver on-time multiple projects as needed.
- Masters or Engineering Degree in a quantitative discipline such as data science, mathematics, statistics, or operations research, from a Tier 1 Institute.
- Strong written communication skills along with good organizational, analytical, quantitative, oral are essential for the role.
- Ability to develop strong working relationships with teammates as well as executives.
- Internal/External Audit experience preferred but not required
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