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Navy Federal Credit Union
Navy Federal Credit Union
H1B Visa SponsorBankingDefenseInsurance
Navy Federal Credit Union is a member-owned financial institution serving more than 14 million members, primarily from the Armed Forces, Department of Defense, veteran communities, and their families. As the world’s largest credit union, it provides banking and financial services through a workforce of more than 24,000 employees across campuses and over 360 branches. Its career opportunities support the organization’s mission of delivering high-quality service to its members, with an emphasis on meaningful work experiences and competitive employee benefits.
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Senior Quantitative Risk Analyst, Internal Audit and AI Governance

Senior quantitative risk analyst leading internal audit reviews of machine learning, generative AI, agentic AI, and model governance at Navy Federal Credit Union. The role combines quantitative analysis, technical assessment, and risk advisory work.

USUnited StatesFLFloridaVAVirginia
$115,600 – $181,200 / year
HybridFull-timeSeniorEnglish RequiredArtificial Intelligence
AWSAzureHadoopPythonSQL

Description

  • Deliver independent assurance on data science, machine learning, generative AI, and agentic AI capabilities through audits and technical reviews.
  • Review model, AI, and data governance frameworks, lifecycle controls, and oversight effectiveness.
  • Analyze risks arising from model complexity, uncertainty, and operational performance.
  • Lead quantitative analyses that support risk management activities.
  • Provide subject-matter expertise in model design, data-driven experimentation, and scalable analytical solutions.
  • Advise Internal Audit colleagues, senior leaders, and business partners on AI and model lifecycles, data governance, regulatory expectations, and industry practices.
  • Lead audits covering the design, development, validation, and implementation of quantitative models, analytics strategies, and AI products.
  • Assess model and AI product performance, scalability, robustness, bias, sensitivity, and risk.
  • Work with cross-functional teams to evaluate business alignment, technical feasibility, and implementation priorities.
  • Coach junior colleagues in modeling methods, coding practices, documentation, and analytical communication.
  • Create reusable frameworks, technical standards, and best practices for quantitative analytics in Internal Audit.
  • Explain complex concepts, tradeoffs, and recommendations to senior stakeholders.
  • Find high-value analytical opportunities and methods for complex, ambiguous problems.
  • Manage increasingly complex projects with moderate supervision and independent judgment.

Requirements

  • Bachelor’s degree in analytics, mathematics, statistics, computer science, data science, operations research, economics, finance, or a comparable combination of education, training, and experience.
  • At least five years of experience in analytics, mathematics, statistics, computer science, data science, operations research, economics, or finance.
  • Comprehensive knowledge of the relevant business area or specialization.
  • Advanced expertise in quantitative modeling, optimization, statistical inference, machine learning, simulation, or algorithm design.
  • Strong programming ability and experience developing production-quality analytical tools, data pipelines, models, or decision-support systems.
  • Ability to direct complex analyses from problem definition through implementation and stakeholder adoption.
  • Strong communication, influencing, and consultative problem-solving capabilities.
  • Experience evaluating and challenging model risk management, data governance, and AI or agentic AI governance.
  • Understanding of models and modeling practices used in credit risk, fraud detection, BSA/AML, operations, treasury and finance, and marketing.
  • Knowledge of model-risk regulatory guidance, including SR 11-7, SR 26-2, and ASOP 56.
  • Knowledge of AI governance frameworks, including the NIST AI Risk Management Framework and ISO/IEC 42001.
  • Knowledge of regulations and frameworks including CECL, CCAR, BSA/Anti-Money Laundering, ECOA, and FCRA.
  • Skills in programming, data modeling, simulation, and advanced mathematics.
  • Familiarity with SQL, R, Python, Hadoop, or SAS.
  • Knowledge of AI platforms and data ecosystems such as Microsoft Copilot Studio, Azure AI Foundry, AWS, Databricks, and Power BI.
  • Authorization to work in the United States without current or future sponsorship.

Benefits

  • Highly competitive compensation.
  • Generous benefits and additional perks.
  • Meaningful opportunities to build career experience.
  • An energized, engaged, and committed workplace culture.
  • Eligibility for the employee referral program.

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