VP, Model Validation and Validation COE

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The VP, Fraud/GEN AI Validation COE is responsible for performing model validation for all fraud models, ensuring they meet the related MRM policies, standards, procedures, and regulations (SR 11‑7). Additionally, the role establishes and maintains a validation Center of Excellence to support the Model Governance team in designing the quality assurance process and leading the execution across all validations. This COE acts as an incubation center for testing and running innovation, provides standardized training and staff development, and supports improving the model risk professional practice to enhance stakeholder experience.

Candidate responsibilities are divided between model validation and the validation COE:

• GEN AI Model Risk Management
  :
  Lead the creation and implementation of a comprehensive end‑to‑end governance framework for generative AI models, including standards, procedures, documentation templates, and processes to manage risks such as hallucination, accuracy, and bias.
• Quality Assurance and Capacity Planning
  :
  Establish and maintain a успех process to review and assess validation practices, proactively identify gaps, and provide guidance on best practices to strengthen the overall validation framework.
• Strategy & Innovation
  :
  Serve as an incubation center to explore, test, and implement innovative approaches leveraging generative AI capabilities to accelerate and improve model validation processes.
• Professional Practice
  :
  Support the Model Governance team to improve 1
  
  LOD model owner experience and deliver value‑focused validation practice.

Model Validation

• Accountable for all fraud model risk management and drive timelines and project completion with minimal guidance.
• Supervisory role working with junior reviewers on validation projects.
• Handle escalation of issues and dispute resolution with model owners independently, ensuring issue remediation, root‑cause analysis, and risk acceptance.
• Support regulatory examinations and internal audits of the modeling process and selected model samples.
• Perform other duties and/or special projects as assigned.

• 5+ years of experience in acquisition/transaction fraud model development or model validation in financial services; experience in CI/CD frameworks preferred.
• Experience in generative AI model validation, framework development, or complex use‑case development.
• Proven experience
  
  Encuén? as automation of validation processes using AutoML, generative AI, and related tools, including design and build of necessary infrastructure.
• Master’s degree in Statistics, Mathematics, Data Science, or related quantitative field; or 9+.lista Main equivalent experience in model development/validation within banking or retail.
• 4+ years hands‑on experience with data science and statistical tools such as Python, Spark, Data Lake, AWS Sage Maker, H2O, and SAS.
• 4+ years of machine learning experience, including handling large datasets and trend analysis.
• 4+ years applying U.S. regulatory requirements for Model Risk Management.
• Ability and flexibility to travel for business as required.

• Strong knowledge of Model Risk Management regulatory requirements with a proven track record of compliance delivery.
• Experience in people and project management, including developing actionable plans, executing effectively, and meeting deadline‑driven objectives.
• Familiarity with credit card and consumer finance products and business models.
• Excellent written and oral communication and presentation skills.

The salary range: $ – $ USD annual, with an annual bonus based on individual and company performance. Actual compensation will be based on work experience, skill level, or knowledge. Salaries are adjusted for markets in CA, NY metro, and Seattle.

• You must be 18 years or older.
• You must have a high school diploma or equivalent.
• You must be willing to take a drug test, submit to a background investigation, and submit fingerprints as part of onboarding.
• You must be able to…