Overview Responsible for overseeing a team of model, data and AI specialists focused on assessing the effectiveness of data governance, data management, model risk management, AI governance and related technology and analytical processes and controls across First Line Management and Second Line Risk Management. Develops audit strategies, ensures high-quality execution of complex audits, and provides deep subject-matter expertise in data and model risk as well as new and emerging areas of artificial intelligence and agentic AI. Aligns audit activities with organizational risk priorities and regulatory expectations. Leads the development and continuous enhancement of risk-based coverage models, testing frameworks, and standardized evaluation criteria-in partnership with Internal Audit leadership-to ensure consistent, repeatable, and risk-sensitive audit approaches across data and model risk areas. Ensures the audit program delivers actionable insights that strengthen risk management, control effectiveness, and operational resilience.
Responsibilities - Lead and manage a team of data and model risk staff responsible for evaluating controls across model development, model validation, model lifecycle governance, data governance, data quality, data lineage, metadata management, and related processes.
- Oversee execution of complex audits, including scoping, planning, fieldwork, issue development, and reporting; ensure audit work meets quality standards, is well-supported, and adheres to professional audit guidance (e.g., IIA Standards).
- Partner with senior Internal Audit leadership and cross-functional teams (e.g., Model Risk Management, Enterprise Data Risk Governance, 1LOD Risk Offices, and Enterprise Technology Services) to understand emerging risks, technology changes, and trends impacting the control environment.
- Translate enterprise risk priorities into targeted audit objectives and risk-based audit plans for data and model risk domains, ensuring alignment with regulatory expectations (e.g., SR 11-7, OCC 2011-12), corporate initiatives, and internal audit methodology.
- Evaluate the adequacy and effectiveness of model lifecycle controls (development, validation, implementation, monitoring, change management, retirement) and data management practices (quality, ownership, access, lineage, metadata, governance committees).
- Lead and mentor teams of data scientists and analysts in developing advanced statistical models, algorithms , and data mining techniques translating business problems into advanced modeling approaches in support business initiatives
- Drive the evolution of our data science practices by implementing best practices in model development, validation, and deployment across various business units
- Collaborate with senior leadership and cross-functional teams to define strategic objectives, establish key performance indicators (KPIs), and prioritize projects that deliver actionable insights to the organization
- Communicate complex data-driven insights in a clear and concise manner to diverse audiences, fostering understanding and buy-in from stakeholders at all levels
- Manage multiple teams and/or specialized units to include resource planning, ensuring the execution of complex modeling initiatives; partner with leaders in analytics, engineering, and business domains to integrate models into workflows
- Analyze large complex datasets to extract actionable insights and present findings to stakeholders, using effective visualization and storytelling techniques
- Review complex code and analyses to ensure accuracy, scalability, and ethical alignment
- Ensure the continuous improvement of data quality and governance processes by collaborating with data engineering and IT teams
- Ensure appropriate use of advanced statistical techniques techniques and manage model lifecycle governance
- Develop and manage budgets related to initiatives, ensuring effective resource utilization and alignment with organizational goals
- Coach teams on cutting-edge data science methods and foster a culture of experimentation and curiosity
- Research, evaluate, and integrate new data science technologies and methodologies to enhance the team's capabilities and drive innovation
Qualifications - Bachelor's degree in related field or equivalent combination of training, education and experience
- College/university degree and 7+ years work experience; 3+ years of management experience
- Strong ability to create an environment that emphasizes data-driven decision-making across an organization, empowering teams to leverage analytical insights effectively
- In-depth knowledge of data science tools and technologies (e.g., Python, R, TensorFlow, SQL) to guide team workflows and methodologies
- Strong presentation and storytelling skills to distill complex models and predictions into understandable insights for diverse audiences, including non-technical stakeholders
- Skill in establishing clear metrics and performance indicators to monitor the effectiveness of data science projects and ensure alignment with business outcomes
- Strong ability to manage multiple teams, ensuring alignment and cohesion in achieving objectives
- Expertise in managing projects from conception to execution, ensuring adherence to timelines and budgets
- Ability to analyze diverse data and identify trends to inform decision-making and strategic planning
- Excellent communication skills, able to convey complex ideas and strategies to various audiences
- Flexibility to adapt strategies and processes in response to evolving business conditions or challenges
- Commitment to fostering team growth through training, feedback, and recognizing achievements
Desired Qualifications- Master's Degree in related field or equivalent combination of training, education and experience
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
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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.
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