I am currently working with a client hiring at the Associate and VP level on their Artificial Intelligence Review and Challenge team. In this role you will be responsible for performing independent review and challenge of all lifecycle activities of AI/ML applications. Candidates should have an advanced degree in a quantitative field and in-depth technical knowledge of AI/ML techniques and associated risks along with 3+ years of experience with AI/ML applications/models in areas such as cybersecurity, NLP, image/voice recognition, and robotic process automation.
Responsibilities:
- Provide independent review and effective challenge on the soundness and fit-for-purpose of AI/ML applications
- Manage AI/ML risk across all life-cycle activities including initial review, ongoing monitoring, and periodic reviews
- Conduct analysis and prepare detailed technical documentation reports sufficient to meet regulatory guidelines and exceed industry standards
- Identify weaknesses and limitations of AI/ML objects and inform stakeholders of their risk profile and recommend compensating controls
- Communicate results to diverse audiences such as AI/ML object owners and developers and senior management
- Manage stakeholder interactions with AI/ML developers and owners across the review lifecycle
- Provide guidance to junior reviewers as and when necessary
- Contribute to strategic, cross-functional initiatives within the model risk management organization
Qualifications:
- Advanced degree (Master's and above) in the fields of mathematics, statistics, computer science, engineering, data science, AI/ML, etc.
- Experience / familiarity with AI / ML applications in areas such as cybersecurity, chatbot, natural language processing, image / voice recognition, robotic process automation
- In-depth technical knowledge of common AI/ML techniques and strong understanding of risks associated with AI/ML and corresponding mitigants
- Ability to collaborate with peers and stakeholders with various background, and to effectively explain technical terms to audience with different levels of technical knowledge
