Lead Business Intelligence & AI Solutions Analyst – Single Family

Fannie Mae • Plano, TX

1d • $123,000 - $161,000 • Onsite

About The Position

As a Lead Associate on the Collateral Strategy & Innovation team, you will help shape the future of Fannie Mae's collateral and valuation capabilities through data, analytics, technology, and artificial intelligence. This role is ideal for someone who combines strong analytical thinking with hands-on technical capability and can translate between business needs, data, and technology. You will contribute to strategic initiatives spanning appraisal and valuation modernization, collateral data and platforms, workflow and process improvement, and the responsible application of AI and automation. As a valued colleague on our team, you will lead complex analysis, help translate business challenges into actionable requirements and solutions, and guide the development of applications and business intelligence capabilities. You will partner across Business, Product, Technology, Analytics, Policy, and other teams to move innovative concepts from exploration through implementation.

Requirements

• Bachelor’s degree or equivalent relevant experience.
• Demonstrated experience using data and analytics to solve complex business problems and develop actionable insights.
• Strong SQL skills and experience analyzing complex datasets.
• Hands-on experience with Python, R, or comparable analytical/programming tools.
• Experience with business intelligence and data visualization tools.
• Experience translating business problems into analytical approaches, requirements, or technology solutions.
• Demonstrated ability to lead complex work and collaborate effectively across business and technical teams.

Nice To Haves

• Experience with artificial intelligence, generative AI, machine learning, automation, or other emerging technologies.
• Experience developing prototypes, proofs of concept, analytical tools, or automated solutions.
• Experience with mortgage lending, collateral risk, appraisal, property valuation, real estate data, or housing finance.
• Familiarity with appraisal modernization, UAD 3.6, Collateral Underwriter®, appraisal alternatives, or related valuation technologies.
• Experience with process improvement, technology implementation, or evaluating data and technology capabilities.

Responsibilities

• Lead complex analysis using structured and unstructured data to identify trends, risks, opportunities, and actionable business insights.
• Apply SQL, data analysis, and visualization skills to explore data, test hypotheses, evaluate outcomes, and support decision-making.
• Use Python, R, or comparable analytical tools to perform analysis, automate repeatable work, prototype solutions, and evaluate new capabilities.
• Identify and evaluate practical applications of artificial intelligence, generative AI, machine learning, and automation to improve collateral decisioning, efficiency, quality, and customer outcomes.
• Develop prototypes and proofs of concept to test ideas and demonstrate business value.
• Translate complex business problems into clear requirements, analytical approaches, data needs, and technology capabilities.
• Analyze processes and systems to identify root causes, control gaps, manual work, and opportunities for simplification or automation.
• Partner across Product, Technology, Analytics, Policy, Operations, and other stakeholders to advance modernization initiatives from discovery through implementation.
• Support appraisal and valuation modernization initiatives involving collateral data, valuation platforms, property data, UAD 3.6, appraisal alternatives, and emerging capabilities.
• Communicate complex analytical and technical findings clearly and influence decisions across technical and non-technical audiences.

Benefits

• Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being.
• Fannie Mae incentive program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior