Conduct independent tests and develop benchmark models that serve as reference points for evaluating model performance. Evaluate the risks associated with machine learning and deep learning models by systematically identifying potential vulnerabilities and recommending mitigation strategies to minimize model risk. Draft and review documentation related to model reviews. Mentor and train junior team members, sharing best practices and supporting their professional development. Stay current with advancements in AI/ML algorithms and fraud detection techniques, incorporating new insights and technologies into the model validation process. Guide model developers and business partners through model risk governance requirements and processes. Coordinate and lead governance activities for the team such as performance monitoring and the annual status assessment, to ensure ongoing model integrity and compliance. Assess and challenge model design and implementation to ensure alignment with risk management and regulatory requirements. Oversee the end-to-end model risk lifecycle, including validation, performance monitoring, change management, and issue remediation. Provide expert insights and recommendations for model enhancements, and present findings to senior management and key stakeholders. Represent the team in audit and regulatory reviews, ensuring timely and accurate responses to inquiries. Support team development initiatives, including recruiting, hiring, and onboarding new team members.

Conduct independent tests and develop benchmark models that serve as reference points for evaluating model performance.

Evaluate the risks associated with machine learning and deep learning models by systematically identifying potential vulnerabilities and recommending mitigation strategies to minimize model risk.

Draft and review documentation related to model reviews.

Mentor and train junior team members, sharing best practices and supporting their professional development.

Stay current with advancements in AI/ML algorithms and fraud detection techniques, incorporating new insights and technologies into the model validation process.

Guide model developers and business partners through model risk governance requirements and processes.

Coordinate and lead governance activities for the team such as performance monitoring and the annual status assessment, to ensure ongoing model integrity and compliance.

Assess and challenge model design and implementation to ensure alignment with risk management and regulatory requirements.

Oversee the end-to-end model risk lifecycle, including validation, performance monitoring, change management, and issue remediation.

Provide expert insights and recommendations for model enhancements, and present findings to senior management and key stakeholders.

Represent the team in audit and regulatory reviews, ensuring timely and accurate responses to inquiries.

Support team development initiatives, including recruiting, hiring, and onboarding new team members.