Senior Director - Internal Audit - Data Science & AI
Fannie Mae
- Location
- Washington, DC
- Work model
- On-Site
- Level
- Staff
- Posted
- Aug 13, 2026
Skills
About this role
Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.
Job Description
Relocation assistance is available for this job (subject to eligibility and business need) or Remote work may also be available. In this dynamic senior leadership position in Audit, you will lead the AI, Product, and Data Science vision and be responsible for advancing Audit's AI strategy, analytics, automation, and enterprise technology delivery. You will build and scale industry-leading technology solutions that improve audit and overall enterprise risk management quality, efficiency, and insight generation while maintaining a well-managed governance of analytics and technology enablers. Your team will partner across Audit, Technology, Enterprise AI, data science, and risk organizations to architect reusable products in a unified platform to deliver AI-enabled capabilities that strengthen risk detection, continuous monitoring, evidence generation, and control-risk reporting. You will be accountable to build a team with high-performing top talent, delivering measurable efficiency and insight-gains, and positioning Audit as a beacon for innovation across the enterprise. THE IMPACT YOU WILL MAKE The Senior Director - Audit AI, Product and Data Science role will offer you the flexibility to make each day your own while working alongside people who care so that you can deliver on the following responsibilities: Lead the development and execution of Audit's AI, analytics, and automation roadmap in alignment with Board goals, Audit priorities, and the broader enterprise AI vision. Own the strategy, product roadmap, delivery, and adoption of AI, GenAI, analytics, and automation capabilities that produce measurable efficiency, quality, and insight gains across the audit lifecycle. Partner with Technology to architect and scale a unified audit platform that enables reusable data assets, analytics, automation, GenAI services, model operations, secure delivery, and enterprise-grade controls. Build destination talent by attracting, developing, and retaining high-performing data science, AI engineering, product, and automation professionals while upskilling the existing audit workforce. Serve as a strategic thought leader to Audit executives and VP+ stakeholders, challenging the organization to maximize value from AI and advanced analytics while managing data, model, operational, and ethical risks. Shape a platform-based approach that reduces time to market, increases reuse, and allows auditors to focus on work requiring professional judgment while AI supports anomaly detection, full-population testing, evidence generation, actionable insights, and control-risk reporting. Collaborate with Enterprise AI, data science, technology, risk, compliance, and business leaders to extend Audit-built capabilities across the three lines of defense and improve enterprise risk management effectiveness. Enable continuous monitoring, more robust risk detection, automated evidence generation, and deeper data-driven insights that establish Audit as a beacon of innovation and a destination for technical and future-skilled audit talent. THE EXPERIENCE YOU BRING TO THE TEAM Minimum Required Experiences 8 years of relevant experience in data science, AI, analytics, automation, product management, technology delivery, audit technology, or related enterprise technology functions. 5+ years of leadership experience building, coaching, and leading high-performing, diverse teams of data science, AI, automation, product, and technology professionals. Proven track record delivering enterprise AI, analytics, automation, or data products from strategy through production adoption with measurable business outcomes. Experience