Model Risk Analyst

About Us

How This Role Impacts Live Oak and Its People

As a Model Risk Analyst, you help ensure Live Oak’s models and AI-enabled solutions are sound, well-governed, and aligned with business objectives and regulatory expectations. Working within the second line of defense, you provide independent review, effective challenge, and ongoing oversight across the full model and AI lifecycle. Your work supports safe and sound operations and informed decision-making across the model and AI lifecycle.

Location: Required to be location in North Carolina market. Work Sponsorship is not supported now or in the future.

What You’ll Do at Live Oak

Model Validation & Effective Challenge

• Conduct quantitative and qualitative validations of internally developed and vendor-provided models, assessing conceptual soundness, data, assumptions, methodology, outcomes, and limitations.

• Review and challenge ongoing monitoring results to confirm models continue to perform as intended, and escalate emerging risks.

• Assess model change requests, including methodology changes, data updates, and enhancements, and help determine the appropriate level of review.

• Provide effective challenge to model owners and developers by identifying risks, limitations, and control gaps, and recommending remediation.

• Document findings, assign criticality, and track remediation through to closure.

AI Governance & Emerging Technology

• Test, evaluate, and independently review AI-enabled tools, agents, and skills to confirm alignment with governance standards, regulatory expectations, and business objectives.

• Assess key AI-specific risks such as bias, data privacy, and reliability, and support monitoring practices for AI-enabled tools and systems.

• Monitor emerging AI tools and industry trends to help flag governance and risk considerations early as new use cases are adopted.

Analysis & Reporting

• Analyze quantitative and qualitative data to identify trends, anomalies, performance concerns, and emerging risks affecting model effectiveness and decision-making.

• Produce clear, well-structured validation, monitoring, and analytical documentation that communicates technical findings to technical and non-technical audiences.

• Support development of risk dashboards, key risk indicators, and executive reporting.

Governance, Framework & Stakeholder Support

• Support the model and AI governance framework by handling intake reviews, risk tiering, validation scheduling, and findings tracking, and by maintaining the model and AI inventory.

• Contribute to governance materials and reporting for committees such as the Model Risk Committee and AI Governance Forum.

• Maintain a current understanding of model risk governance, policies, procedures, and regulatory guidance, including SR 26-2 and emerging AI/ML governance expectations.

Required Experience

• Bachelor’s degree in Statistics, Mathematics, Economics, Finance, Engineering, Data Analytics, Computer Science, or a related quantitative field.

• 2–4 years of experience in model risk management, model validation, model development, quantitative analytics, or a related risk management function within financial services.

• Experience reviewing or validating quantitative and/or qualitative models, such as credit risk, allowance, forecasting, pricing, BSA/AML, or operational models.

• Ability to analyze model documentation, data, assumptions, methodologies, and results, and to apply independent judgment and effective challenge.

• Baseline familiarity with AI or machine learning concepts and related governance considerations.

• Proficiency with Python and SQL, and hands-on experience with version-control and analytical platforms such as GitHub and Databricks.

• Strong written and verbal communication skills, able to convey complex concepts to varied audiences.

• Well-organized and self-directed, with intellectual curiosity and a proactive, collaborative approach to managing competing priorities.

Preferred Experience

• Advanced degree (Master’s) in a quantitative discipline.

• Knowledge of banking products, financial services, and model risk management practices.

• Experience evaluating AI, machine learning, or agentic/LLM-based systems and their governance considerations.

• Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework or emerging interagency guidance.

• Experience with additional analytical tools such as R or SAS.

• Experience developing risk dashboards, key risk indicators, and executive reporting.

Our Values

• Dedication: Possess a deep commitment to Live Oak Bank’s mission and core values, exemplified through a strong work ethic, adaptability and pride in your work.

• Ownership: Take initiative to deliver positive results by proactively and creatively solving problems, while maintaining a high degree of quality.

• Respect: Treat everyone with courtesy, politeness, and kindness.

• Innovation: Embrace fresh ideas and fearlessly contribute new solutions to emerging or existing problems.

• Teamwork: Foster collaboration, accountability, and trust with others and understand that together, we do more

For a detailed overview of our employee benefits please visit:

Live Oak Bank is an Affirmative Action and Equal Opportunity Employer, Minorities/Women/Veterans/Disabled. We consider applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, veteran status or disability. Equal access to programs, service and employment is available to all persons. Those applicants requiring reasonable accommodation to the application and/or interview process should notify human resources at [email protected].

EEO is the Law

The base pay range for this position is $82,240.00 - $133,640.00 per year. Compensation may also include annual bonuses and long-term incentives, subject to various metrics and company policy. A candidate’s salary is determined by several factors including travel, relevant work experience or skills and expertise.

Please note that we provide at least the minimum requirement of paid sick leave to our employees who reside in states that require employer-paid sick leave, including but not limited to Arizona, California, Colorado, District of Columbia, Maine, Maryland, Massachusetts, Michigan, Nevada, New Jersey, New Mexico, New York, Oregon, Rhode Island, Vermont, and Washington.