Audit Data Science Advisor

Fannie Mae; United States; On-site; USD 155,000 - 209,000; Full time

Job summary

Fannie Mae in the United States is seeking a skilled data scientist with a minimum of 6 years of experience in data science, machine learning, and AI development. The role involves developing advanced analytics solutions and building a unified Audit platform to support business objectives.

The ideal candidate holds a Master’s degree in Data Science or related fields and is proficient in Python, AWS data services, and analytical techniques. A competitive compensation range of $155,000 to $209,000 is offered.

Qualifications

• Minimum of 6 years of experience in data science and AI.
• Strong proficiency in Python and data science techniques.
• Experience in Internal Audit or Risk Management is a plus.

Responsibilities

• Develop advanced analytics and AI solutions.
• Build a unified Audit platform with reusable data.
• Provide thought leadership on analytics applications.

Skills

Data science

Machine learning

Python

AWS data services

Analytical skills

Technical communication

Education

Master’s degree in Data Science or related field

PhD in Data Science or related field

Tools

AWS Redshift

AWS Athena

AWS S3

Job description

Overview

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. 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.

Responsibilities

• 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.
• 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 address 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.

Experience and Qualifications

• Minimum of 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 Redshift, Athena, S3, and AWS Data Wrangler.
• Strong analytical skills to support testing, validation, model assessment, and business decision-making.
• Strong communication skills, including the ability to explain technical concepts and solutions to non-technical partners and stakeholders.
• Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.
• PhD in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience (desired).
• Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated environments (desired).
• Experience applying advanced data science methods such as regression, SVM, random forests, and neural networks (desired).
• Strong technical writing, presentation, and executive stakeholder communication skills (desired).
• Proven ability to influence and collaborate across cross-functional teams, including Audit, Technology, AI, and Risk partners.
• Experience with AI engineering tools and patterns, such as Anthropic or OpenAI models and tool‑calling frameworks (desired).

Compensation

Requisition compensation: 155,000 to 209,000.

Equal Opportunity Employer

Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless providing such accommodations would cause undue hardship to the company.