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Model Risk Governance Jobs (NOW HIRING)

NC SECU

Model Risk Governance Manager

Raleigh, NC · Hybrid

Partner with technology, privacy, operational, and compliance risk leaders to ensure AI risk practices are well-integrated. * (10%) Manage and develop model risk and AI risk governance staff. * (10%) ...

BOK Financial

Model Risk Governance Officer

Tulsa, OK · On-site

As a Model Risk Governance Officer, you'll work across the bank to evaluate models, provide independent challenge, and deliver insights that help leaders operate within the organization's risk ...

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How much do model risk governance jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for model risk governance in the United States is $45.71, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $72.12 per hour, depending on experience, location, and employer.

What are some typical challenges faced in a Model Risk Governance role?

Professionals in Model Risk Governance often encounter challenges such as keeping up with evolving regulatory requirements, ensuring comprehensive documentation for models, and maintaining effective communication between technical modelers and business stakeholders. Balancing rigorous model validations with tight project timelines can also be demanding, especially when coordinating input from various teams. Overcoming these hurdles requires a proactive approach to learning, strong organizational skills, and the ability to translate complex quantitative issues into actionable insights for decision-makers. These challenges make the work dynamic and offer significant opportunities to influence critical risk management processes within the organization.

What is a Model Risk Governance job?

A Model Risk Governance job involves overseeing the policies, procedures, and frameworks used to manage model risk within an organization. Professionals in this role ensure that models used for decision-making in areas like finance, risk management, and compliance are properly validated, monitored, and updated. They work closely with model developers, risk managers, and regulators to enforce governance standards and mitigate potential risks. Key responsibilities include establishing model validation processes, conducting risk assessments, and ensuring compliance with regulatory requirements.

What are the key skills and qualifications needed to thrive in the Model Risk Governance position, and why are they important?

To excel in Model Risk Governance, you typically need a strong background in quantitative finance, statistics, or a related field, often with advanced degrees such as a master's or Ph.D., and experience in risk management. Familiarity with model validation tools, programming languages like Python or R, and regulatory frameworks such as SR 11-7 or Basel guidelines is highly valued. Strong analytical thinking, communication skills, and the ability to manage multiple stakeholders are key soft skills for this position. These competencies ensure effective oversight of model risk, facilitate regulatory compliance, and enable clear communication of complex technical issues to non-technical stakeholders.

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What cities are hiring for Model Risk Governance jobs? Cities with the most Model Risk Governance job openings:
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Model Risk Governance jobs near you
Infographic showing various Model Risk Governance job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 85% Full Time, 13% Part Time, and 1% Contract. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $95,086 per year, or $45.7 per hour.

Model Risk Governance Manager

NC SECU

Raleigh, NC • Hybrid

Full-time

Posted 6 days ago

Job description

If you are motivated and believe in the credit union philosophy of "People Helping People," join our team!

Essential Responsibilities:

  • (30%) Development and execution of policies, standards, and internal procedures for all phases of the model and AI life cycle, including identification, risk assessment, definition of control objectives, ongoing monitoring, and retirement.
  • (20%) Ownership of the model risk management framework and reporting on model governance, development, validation, and monitoring for the organization. Responsible for creating and ongoing reporting of key risk indicators and management reporting for senior risk management stakeholders, management committees, and board-level committees.
  • (20%) Design and maintain AI governance frameworks, standards, and research to guide responsible AI adoption. Embed responsible, transparent, and controlled AI practices across the full AI life cycle, from design and development to deployment and monitoring. Ensure that AI capabilities are delivered safely, ethically, and in alignment with regulatory expectations, while enabling speed, scalability, and business value. Partner with technology, privacy, operational, and compliance risk leaders to ensure AI risk practices are well-integrated.
  • (10%) Manage and develop model risk and AI risk governance staff.
  • (10%) Ensure overall compliance of the program with regulatory guidance on model risk management and artificial intelligence, staying current with changes in regulatory expectations and leading industry practices.
  • (10%) Provide training and communication around the expectations of the MRM program and AI risk management to stakeholders across the organization.

Required Education & Experience (Knowledge, Skills, & Abilities):

  • Masters in a quantitative discipline (Economics, statistics, finance, data science or analytics, math, physics, or related field).
  • 5+ years of experience in modeling or analytics, including experience developing enterprise-wide policies, standards and protocols in model risk, AI, or a related discipline.
  • Ability to understand model conceptual design, testing of performance, controls over data flows, and compliance of model results with intended application.
  • Must possess a deep understanding of regulatory guidance and expectations in Model Risk Management (e.g., SR 26-2, SR 15-19) and Artificial Intelligence (e.g. NIST AI Risk Management Framework, ISO 42001).
  • Programming skills in a statistical programming language, such as SAS, R, or Python. Ability to independently write computer code to perform analysis on complex modeling and analytical challenges and to review code written by others for accuracy and efficiency.
  • Subject matter expertise in advanced mathematical and statistical modeling techniques, such as competing risk logistic regression, time series analysis, ordinary least squares, Monte Carlo simulation, and machine learning techniques (e.g. XGBoost).
  • Excellent oral and written communication skills. Experience writing and reviewing detailed technical validation reports and/or model development documentation.
  • Familiarity with modern artificial intelligence (AI), including large language models (LLMs), retrieval augmented generation, generative AI, agentic AI, and the approaches and architecture required to harness and manage the risks of these tools.
  • Strong attention to detail and the ability to independently formulate solutions to complex modeling and analytical challenges without existing procedures or precedent. Ability to mentor staff through complex analytical challenges and difficult technical conversations with internal and external stakeholders.
  • Ability to evaluate model risks, weigh pros and cons of risk mitigation, and communicate very technical concepts in plain language.
  • Perform job functions independently with limited day-to-day oversight from supervisor.

Preferred Education & Experience (Knowledge, Skills, & Abilities):

  • Experience managing teams of technical individual contributors and/or external vendors performing technical modeling work
  • Experience in financial services or consulting industry
  • Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR, ALM, loan pricing and/or mortgage servicing rights, derivatives, Compliance (BSA/AML/OFAC), Liquidity, or Fraud
  • Subject matter expertise in generative large language models (Artificial Intelligence)
  • FRM or CFA certification

Job Environment & Physical Requirements:

  • Hybrid expectations
  • Sitting for prolonged periods
  • Computer for prolonged periods

SECU provides equal employment opportunity to all qualified persons regardless of race, color, religion, age, sex, sexual orientation, gender identity, national origin, genetic information, disability, veteran status, or other classification protected by law.

Disclaimer

State Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.

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