Senior Director, Model Risk Management
Equifax
full-time
Posted on:
Location Type: Hybrid
Location: Alpharetta • United States
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Job Level
About the role
- Lead, manage, and mentor a high-performing team of data scientists and reviewers, providing expert oversight for both Generative AI application review and rigorous model validation projects
- Oversee the execution of multiple complex validation projects simultaneously, from test design to final delivery and communication
- Serve as the primary technical lead for validating GenAI safety
- Direct team members in identifying and mitigating complex risks such as model hallucinations, prompt injection, and data leakage
- Foster a culture of critical thinking, continuous improvement, and effective risk management within the team
- Collaborate with global partners to supervise validation projects, ensuring a consistent and technically sound approach to AI/Model Risk Management across non-direct reporting lines
- Conduct deep-dive research into emerging analytical techniques and "LLM-as-a-judge" evaluation methods to stay ahead of the curve in validating Agentic AI and other non-deterministic systems
- Develop and execute comprehensive validation test designs to assess model soundness and identify potential risks
- Critically assess the completeness and accuracy of model documentation, code, and marketing materials
- Develop and implement innovative validation approaches for complex and nontraditional models, including those with unstructured data and unique risk profiles
- Serve as a trusted advisor to model developers, engineers, and business owners, providing expert guidance on model design, development and AI safety-by-design
- Review and provide guidance on model monitoring plans and ongoing performance reports
- Drive the enhancement of Model Risk Management procedures and standards to align with evolving regulatory requirements and industry best practices
- Collaborate with key stakeholders across the organization, including marketing, technology, legal, compliance, and business owners, to ensure a robust model risk governance framework.
Requirements
- Master’s degree in a quantitative field such as statistics, data science, computer science, mathematics, economics, or finance
- A PhD is strongly preferred
- 7-10 years of industry experience in predictive modeling, data science, or a related quantitative field
- Prior experience with credit risk model development and/or validation is highly preferred
- A minimum of 3 years of experience managing a highly talented team with 6 or more direct reports is preferred
- Strong knowledge of and hands-on experience with a broad spectrum of modeling techniques, ranging from traditional statistical methods (e.g., Logistic Regression, Time Series, XGBoost) to advanced architecture including Deep Neural Networks
- Generative AI, and Agentic AI frameworks are highly preferred
- Extensive experience with Big Data environments and advanced computational processes
- Demonstrated experience with model risk management and/or compliance is highly preferred
- Proven ability to quickly grasp complex concepts and identify potential model issues or validation gaps
- Proficiency with programming languages such as SAS, SQL, R, Python, Scala, and Spark
- Hands-on experience with UNIX/LINUX and Google cloud environments.
Benefits
- Comprehensive compensation and healthcare packages
- 401k matching
- Paid time off
- Organizational growth potential through our online learning platform with guided career tracks
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
predictive modelingdata scienceLogistic RegressionTime SeriesXGBoostDeep Neural NetworksGenerative AIAgentic AImodel risk managementcompliance
Soft skills
leadershipmentoringcritical thinkingcontinuous improvementrisk managementcollaborationcommunicationproblem-solvingadvisory skillsteam management
Certifications
Master’s degreePhD