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Director Model Risk Governance Jobs in Washington

Freddie Mac

Data Governance Senior

Mclean, VA · On-site

... Model (ABM) lifecycle from design through approval. Qualifications: * 5 - 7 years of information risk / data governance experience within the financial services industry. * Bachelor's degree or ...

Freddie Mac

Data Governance Senior

Mclean, VA

... Model (ABM) lifecycle from design through approval. Qualifications: * 5 - 7 years of information risk / data governance experience within the financial services industry. * Bachelor's degree or ...

World Bank

Senior Program Assistant

Washington, DC · On-site

... model inventory, and implementing amodel risk governance framework, standards, and controls ... Provide high-level executive and administrative support to the Director, including calendar ...

Visa

Director, VCA NA Risk Practice

Ashburn, VA · On-site

Develop customer lifetime value (CLV) and portfolio economics models to inform acquisition ... Collaborate crossfunctionally with Product, Engineering, Risk Governance, Legal, Compliance, and ...

Pwc

AI Governance Sr Associate

Washington, DC · On-site

$72K - $212K/yr

... risk frameworks such as NIST and ISO - Supporting the design and assessment of AI governance models ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

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Director Model Risk Governance information

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 model risk governance?

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 is a director model risk governance?

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 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.
What are the most commonly searched types of Model Risk Governance jobs in Washington? The most popular types of Model Risk Governance jobs in Washington are:
What are popular job titles related to Director Model Risk Governance jobs in Washington? For Director Model Risk Governance jobs in Washington, the most frequently searched job titles are:
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What cities in Washington are hiring for Director Model Risk Governance jobs? Cities in Washington with the most Director Model Risk Governance job openings:
Director Model Risk Governance jobs near you
Infographic showing various Director Model Risk Governance job openings in Washington as of August 2026, with employment types broken down into 2% As Needed, 81% Full Time, 15% Part Time, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Senior Data Scientist (Internal Audit Model & AI Risk)

Navy Federal Credit Union

Vienna, VA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Navy Federal Credit Union rating

8.1

Company rating: 8.1 out of 10

Based on 274 frontline employees who took The Breakroom Quiz

59th of 150 rated financial services

Job description

Overview

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.


Navy Federal's Internal Audit team is in the midst of an exciting transformational journey to become a best-in-class Audit function! It is our vision to be a preferred advisor to the business by building and cultivating trust through the consistent execution of high-quality and risk-focused audit and advisory work. We're focused on implementing efficient processes, maximizing our use of technology, integrating data analytics into everything we do, and investing in our biggest asset, our people. If this sounds like the type of team you'd like to be a part of, then we want to learn more about you!


Support Internal Audit's evaluation of model and artificial intelligence (AI) risk and governance frameworks and their ability to mitigate risk at the individual implementation and aggregate levels. Conduct reviews of complex data science and machine learning models across the organization through audit engagements and technical reviews of models. Serve as a subject matter expert to Internal Audit staff, senior management and business partners on end-to-end life-cycle management of model development, implementation, ongoing monitoring, regulatory expectations, and industry modeling practices. Conduct work assignments of increasing complexity, under moderate supervision with some latitude for independent judgment. Intermediate professional within field; requires moderate skill set and proficiency in discipline.


Provide independent assurance through assessments of complex data science, machine learning, generative AI, and agentic AI capabilities across the organization through audit engagements and other technical reviews. Evaluate relevant ecosystems by assessing governance frameworks, risk management practices, AI/model lifecycle controls, the effectiveness of oversight activities across the first and second lines of defense, and the complexity, uncertainty, transparency, and operational risks associated with advanced analytical and AI-enabled solutions. Serve as a subject matter expert to Internal Audit staff, senior management, and business partners on end-to-end lifecycle management of AI/model development, implementation, ongoing monitoring, regulatory expectations, and industry practices. Conduct and manage work assignments of increasing complexity under moderate supervision with some latitude for independent judgment. Intermediate professional within field; requires moderate skill set and proficiency in discipline.


This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you.

Responsibilities

  • Responsible for assessing AI and model governance processes including model inherent risk ratings, model validations, materiality of model changes, ongoing performance monitoring, and other targeted model review approaches as part of model related governance audits.

  • Ability to execute and manage independent internal audit reviews of AI products, AI-enabled systems, and models by leveraging subject matter expertise in AI technologies, model risk, and governance practices. Follow established audit frameworks and assurance processes to deliver high-quality reviews while effectively managing scope, timelines, stakeholder expectations, and communication throughout the engagement lifecycle.

  • Leverages specialized technical approaches to develop, implement, and execute model testing plans for models that require expert model risk knowledge and skills.

  • Evaluates model development, implementation, and use as it pertains to elements of model conceptual soundness, model assumptions, modeling methodology, model limitations, data quality, ongoing monitoring, and other more complex elements of the model development process.

  • Identifies meaningful insights from large data and metadata sources

  • Test hypotheses/models, analyze, and interpret results

  • Exercise sound judgment and discretion within defined procedures and practices

  • Develop and code moderately complex software programs, algorithms, and automated processes

  • Use modeling and trend analysis to analyze data and provide insights

  • Develop understanding of best practices and ethical AI

  • Transform data into charts, tables, or format that aids effective decision making

  • Build working relationships with team members and subject matter experts

  • Lead small projects and initiatives

  • Utilize effective written and verbal communication to document and present findings of analyses to a diverse audience of stakeholders

Qualifications

  • 5-7 years of experience in data analysis, statistical modeling or regression analysis, including language models, LLMs and/or Generative AI technologies

  • Basic understanding of business and operating environment

  • Statistics

  • Programming, data modeling, simulation, and advanced mathematics

  • SQL, R, Python, Hadoop, SAS, SPSS, Scala,

  • Knowledge of AI platforms and ecosystems supporting machine learning, generative AI, and LLM-enabled systems, including Microsoft Copilot Studio, Azure AI Foundry, AWS, and Databricks.

  • Model lifecycle execution including model development, validation, and governance

  • Technical writing

  • Data storytelling and technical presentation skills

  • Research Skills

  • Interpersonal Skills

  • Working knowledge of procedures, instructions, and validation techniques

  • Communication

  • Critical Thinking

  • Collaborate and Build Relationships

  • Initiative with sound judgement

  • Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)

  • Sound Judgment

  • Problem Solving (Responds as problems and issues are identified)

  • Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields


Desired Qualifications

  • Prior experience with model validation/ model risk management, AI and Agentic risk management, enterprise risk management, or internal audit

  • Deep knowledge and experience with SR 11-7 and/or ASOP 56

  • Understanding of various models and modeling practices used in credit risk management, fraud detection, BSA/AML, operations, treasury & finance, marketing models, etc.

  • Knowledge of one or more regulations and frameworks such as CECL, CCAR, Anti-Money Laundering, ECOA, FCRA, NIST AI Risk Management Framework, ISO/IEC 42001Artificial Intelligence Management System, etc.

  • Advanced knowledge of Navy Federal Credit Union instructions, standards, and procedures

  • Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or another quantitative or related field

Additional Information

Hours:

  • Monday - Friday, 8:00AM - 4:30PM

Location:

  • 820 Follin Lane, Vienna, VA 22180
  • 5510 Heritage Oaks Drive, Pensacola, FL 32526
  • 141 Security Drive, Winchester, VA 22602

About Us

Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks. Our approach to careers is simple yet powerful: Make our mission your passion. * FORTUNE 100 Best Companies to Work For 2026 * Yello and WayUp Top 100 Internship Programs 2025 * Computerworld Best Places to Work in IT 2026 * Most Loved Workplace - America's Top Most Loved Workplaces 2025 * 2025 PEOPLE Companies That Care * Newsweek Most Trustworthy Companies in America 2026 * Military Times 2025 Best for Vets Employers * Forbes 2026 America's Best Large Employers * Forbes 2025 America's Best Employers for New Grads * Forbes 2025 America's Best Employers for Tech Workers * 2025 RippleMatch Campus Forward Award Winner for Overall Excellence * Military.com Top Military Spouse Employers 2025 * 2026 Handshake Early Talent Award * Newsweek America's Greatest Workplaces for Culture, Belonging and Community 2026 From Fortune Magazine. 2026 Fortune Media IP Limited. All rights reserved. Used under license. Fortune and Fortune 100 Best Companies to Work For are registered trademarks of Fortune Media IP Limited and are used under license. Fortune Magazine, Fortune Media (USA) Corporation, and its affiliates are not affiliated with, and do not endorse products or services of, Navy Federal Credit Union. Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to age, race, sex, color, religion, national origin, disability, veteran status, pregnancy, sexual orientation, genetic information, gender identity or any other basis protected by applicable law. Accommodations: If you need accommodation or assistance for a qualifying condition to complete the online application (or during any stage of the hiring process), you can contact Navy Federal's Medical Accommodations team at medicalaccommodations@navyfederal.org or by calling 1-888-503-6013. This team cannot provide any information on job postings or application status. Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team's discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position. For additional details regarding compensation and benefits, review the Benefits page of the Navy Federal Career Site. Protect Yourself from Job Scams: Navy Federal Credit Union jobs are posted on our career site, jobs.navyfederal.org and reputable job boards (e.g., LinkedIn, Indeed). We do not post jobs on social media marketplaces, messaging apps or unverified websites. We will never ask candidates for payment, bank details or personal financial information during the hiring process. Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.

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About Navy Federal Credit Union

Sourced by ZipRecruiter

Navy Federal Credit Union, based in Vienna, Virginia, United States, is a significant player in the financial services industry. Their official website is navyfederal.org. With its roots dating back to 1933, it was initially established to provide credit to Navy members. Over the years, Navy Federal has magnified its scope, evolving into a full-service credit union serving all branches of the military, the Department of Defense, veterans, and their families. The company’s core values include integrity, service, education, and leadership. Navy Federal aims to be the most preferred and trusted financial institution serving the military and their families.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Vienna, VA, US

Year founded

1933

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