Model Validation 2nd LOD Lead Analyst

Location: Wilmington, Delaware, United States

Responsibilities

• Provide independent review and effective challenge on the soundness and fit-for-purpose of Generative AI, AI/ML objects.
• Act as a senior model validator to independently manage Generative AI, 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 Generative AI, AI/ML objects and inform stakeholders of their risk profile and recommend compensating controls.
• Communicate results to diverse audiences such as object owners and developers and senior management.
• Manage stakeholder interactions with Generative AI, AI/ML object developers and owners across the review lifecycle.
• Interact with senior levels of management to facilitate understanding of usage of risk models and inform critical decisions.
• Develop NLP and GenAI applications to automate and streamline existing manual validation processes, aiming to increase operational efficiency for the organization.
• Developed state‑of‑art risk management practice, validation guidelines, and testing playbooks for AI/ML (including GenAI) models.
• Lead collaborative efforts with cross‑functional teams (e.g., model development, risk governance, business units) on key AI/ML/GenAI projects and present complex validation findings and strategic recommendations to senior stakeholders and successfully negotiate outcomes.
• Provide structured mentorship for junior validators, focusing on their technical skills, critical thinking, and communication.
• Drive team initiative to streamline a common validation process or improve knowledge sharing.
• Drive the exploration and adoption of at least one innovative methodology or tool to enhance GenAI model validation efficiency or effectiveness.
• Develop internal guidance, best practices document, or training session based on these initiatives.

Requirements

• Master’s degree or foreign equivalent in Statistics, Mathematics, Finance or related field and 3 years of experience