I am currently working with an Artificial Intelligence Review team hiring at the AVP level. 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.
- 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
- Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational. Also, may develop, validate and strategize uses of scoring models and scoring model related policies.
- Uses Predictive modeling methods, Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary.
- Automates data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations.
- Advanced degree (Master's and above) in the fields of mathematics, statistics, computer science, engineering, data science, AI/ML, etc. preferred
- 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
- Proficiency with Python/SQL
- Ability to collaborate with peers and stakeholders with various background, and to effectively explain technical terms to audience with different levels of technical knowledge