Data Scientist II
AIEG (AI Enablement and Governance) is a team within CDSO, that assesses alignment of all AI Solutions to Bank's AI policy. This team is responsible for evaluating all AI Tollgate submissions, residual risk assessments, and fulfilment of any conditions raised prior to deployment of the solutions.
Senior Data Scientist in this role is fully responsible for interfacing with stakeholders across the broader organization and senior business executives, model owners, model developers, solution architects etc., to understand AI solution in the context of a broader business need. The ideal candidate will thrive in a fast paced environment possessing an ability to assimilate information quickly while maintaining focus on risk, accuracy and timeliness. The role requires sound understanding of several functions in Banking and Finance, in-depth understanding of AI/ML, regulations and governance needs, and Bank's internal processes. Furthermore, the role requires excellent executive communication and program management skills where the ability to manage up and around is critical for success. The role provides an opportunity to grow a deeper understanding of several business areas. Key Responsibilities:
- Senior Data Scientist will be responsible for assessing AI (Artificial Intelligence) solutions implemented across the bank (built internally or externally) to identify any risks which may have unintended consequences
- Helps lead and drive AI Governance through efficient and effective administration of AI Policy requirements
- Manages, maintains and oversees AI Tollgate process execution, ensuring that all AI models are assessed for the residual risk.
- Leads and contributes to AI Enablement efforts. Partners with business units in developing innovative, high impact AI use cases and strategic roadmaps. Assists FLUs and development teams to accelerate adoption of AI best practices.
- Critically assesses and challenges AI models on conceptual soundness, assumptions and limitations, data, developmental evidence in support of modeling choices, performance, implementation and documentation
- Understands the core methodology in AI solutions and the context in which it will be deployed so as to find risks/gaps
- Suggests alternative approaches or controls to mitigate risks/gaps identified
- Looks for unexpected risks / unintended consequences of an AI solution over its life cycle
- Assists in evaluating AI Solutions during Tollgate, Risk Assessment & Deployment Signoff processes
- - 7+ years of hands on model risk management, quantitative modelling or banking model development experience (required).
- - Familiarity with model risk management standards and regulation (e.g., SR 11-7) (required).
- - Strong understanding of Banking and Finance products and internal functions. (required)
- - Sound knowledge of financial instruments and financial risk/operational risk management principles is must
- - Prior experience in risk management is desired
- - Good analytical skills to breakdown requirements and establish remediation plans (required).
- - Familiarity with machine learning techniques and algorithms (preferred).
- - PhD in a quantitative field such as Mathematics, Physics, Applied/Quantitative Finance, Engineering or Statistics; or Master's degree in the same field (required).
- - CFA/FRM certifications preferred
- - Attention to detail.
- - Good communication skills.
- - Ability to work across multiple threads.
1st shift (United States of America) Hours Per Week: