Audit Data Science Advisor

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.

As a valued contributor to our team, you will serve as a coach, mentor, and subject matter expert, driving the success of product and initiative workstreams through insights, product and change recommendations, process improvement, automation, and predictive modeling. You will apply deep expertise in data science, machine learning, AI techniques, large-scale data processing, computational programming, and practical problem solving, with the ability to clearly explain technical solutions to non-technical partners and stakeholders. As an advisor, you will partner across Audit, Technology, Enterprise AI, data science, and risk organizations to architect reusable products on a unified platform that delivers AI-enabled capabilities for stronger risk detection, continuous monitoring, evidence generation, and control-risk insights reporting. In addition, you will help shape the organization’s strategy for using and developing AI and data science to deliver data-driven insights and sound business judgment. In addition, you will provide expert guidance on well-governed models and analytical tools, partnering with senior leadership to advance business and AI transformation and innovation. THE IMPACT YOU WILL MAKE The Audit Data Science Advisor 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: Partner across Audit, Technology, and platform teams to build a unified Audit platform with reusable data, analytics, automation, GenAI services, model operations, secure delivery, and enterprise controls. Develop advanced analytics, AI, and data science solutions to solve complex business and technical challenges and shape technical direction. Design, test, and validate audit solutions using advanced data science methods aligned with audit standards and methodology. Apply data science to improve risk measurement, valuation, decision-making, and business performance. Create technical strategies and executive-ready materials that communicate high-impact solutions to leaders and stakeholders. Provide thought leadership on applying advanced analytics and data science to business challenges. Build solutions for continuous monitoring, risk detection, automated evidence generation, and deeper insights. Assess model effectiveness and fitness for use, ensure testing and monitoring, and explain key drivers and limitations. Lead cross-functional teams through the model lifecycle, aligning changes with business goals. Stay current on industry practices, regulations, and internal standards to ensure compliance and escalate issues as needed. Advise senior leaders on priorities, balancing accuracy, speed, cost, and governance. Support the Model Owner and Lead Model User in building consensus, prioritizing requirements, testing changes, resolving findings, and sharing best practices. Drive continuous improvement in modeling and analytics while promoting accountability, transparency, and proactive model risk management. Represent the Analytics team in internal forums, regulatory settings, and industry conferences, sharing best practices and thought leadership. THE EXPERIENCE YOU BRING TO THE TEAM Minimum Required Experiences 6 years of related experience in data science, machine learning, and AI solution development, including GenAI workflows. Master’s degree in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field. Advanced proficiency in Python and core data science and machine learning techniques. Experience building end-to-end data science solutions using AWS data services such as