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Director 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 ...

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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Director Model Risk Governance information

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$54K

$143.2K

$260K

How much do director model risk governance jobs pay per year?

As of Jun 20, 2026, the average yearly pay for director model risk governance in the United States is $143,185.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,500.00 and $167,500.00 per year, depending on experience, location, and employer.

What is the difference between Director Model Risk Governance vs Model Risk Analyst?

AspectDirector Model Risk GovernanceModel Risk Analyst
CredentialsAdvanced degrees (e.g., Master’s, PhD), professional certifications (e.g., FRM, CFA)Bachelor’s or Master’s degree, relevant certifications
Work EnvironmentStrategic oversight, policy development, senior stakeholder engagementData analysis, model validation, risk assessment
Employer & Industry UsageFinancial institutions, banks, asset managersFinancial institutions, risk management teams
Search & Comparison IntentUnderstanding leadership roles in model risk governanceEntry to mid-level model risk roles, analysis tasks

The main difference is that the Director Model Risk Governance focuses on strategic oversight, policy setting, and managing model risk at a senior level, while the Model Risk Analyst handles technical validation, data analysis, and risk assessment tasks. The director role involves leadership and decision-making, whereas the analyst role is more technical and operational.

What are the key skills and qualifications needed to thrive as a Director of Model Risk Governance, and why are they important?

To thrive as a Director of Model Risk Governance, you need deep expertise in quantitative finance, risk management, and model validation, often backed by an advanced degree in a quantitative field and relevant industry experience. Familiarity with risk management frameworks, regulatory standards (e.g., SR 11-7), and proficiency in analytical tools like Python, R, or SAS are typically required. Exceptional leadership, communication, and critical thinking skills help you effectively oversee teams and coordinate with stakeholders across the organization. These competencies are vital to ensure robust model governance, regulatory compliance, and informed risk-based decision-making at the enterprise level.

What are Director Model Risk Governance roles?

Director Model Risk Governance roles are senior positions responsible for overseeing and managing the risks associated with financial and predictive models within an organization. These professionals establish and implement model risk management frameworks, ensure compliance with regulatory requirements, and oversee model validation processes. They collaborate with model developers, validators, and business units to identify, assess, and mitigate model risks, as well as report on governance effectiveness to senior management. Their work is crucial in maintaining the reliability and integrity of models used for decision-making and regulatory reporting.

What are some common challenges faced by a Director of Model Risk Governance, and how can they be addressed?

A Director of Model Risk Governance often encounters challenges such as ensuring consistent model validation across diverse business units, keeping up with evolving regulatory requirements, and fostering effective communication between model owners, validators, and senior management. Addressing these challenges typically involves establishing robust model risk frameworks, maintaining clear documentation, and promoting a culture of transparency and collaboration. Regular training sessions and open forums can help bridge knowledge gaps, while leveraging technology can streamline model inventory and validation processes.
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Director Model Risk Governance jobs near you
Infographic showing various Director Model Risk Governance job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $143,185 per year, or $68.8 per hour.

Model Risk Governance Manager

NC SECU

Raleigh, NC • Hybrid

Full-time

Posted 8 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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