Audit Data Science Advisor

Fannie Mae; Washington (District of Columbia); On-site; USD 155,000 - 209,000; Full time

Benefits offered by this job

Comprehensive benefits package

Health, life, and voluntary lifestyle benefits

Job summary

Fannie Mae is seeking a Data Science expert in Washington, D.C. to drive innovation in housing finance. You will mentor teams, architect solutions, and develop AI-enabled capabilities to enhance risk detection and reporting.

The ideal candidate has extensive experience in data science with strong Python skills and advanced machine learning knowledge. This position ensures compliance and strategic direction in AI and data science within a pivotal role in a stable and supportive environment.

Qualifications

• 6+ years of experience in data science, machine learning, and AI.
• Advanced proficiency in Python and core data science techniques.
• Strong analytical and communication skills.

Responsibilities

• Build a unified Audit platform with automation and analytics.
• Develop advanced analytics and data science solutions.
• Assess model effectiveness and drive continuous improvement.

Skills

Data science expertise

Machine learning techniques

AI solution development

Python expertise

Analytical skills

Communication skills

Education

Master's degree in Data Science or related field

Bachelor's Level Degree

Tools

AWS data services

GenAI workflows

Job description

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.

Job Description

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. You will provide expert guidance on well‑governed models and analytical tools, partnering with senior leadership to advance business and AI transformation and innovation.

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 to raise 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.

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 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.

Desired Experiences

• PhD in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience.
• Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated environments.
• Experience applying advanced data science methods such as regression, SVM (support vector machines), random forests, and neural networks.
• Strong technical writing, presentation, and executive stakeholder communication skills.
• 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.

Qualifications

Education: Bachelor's Level Degree.

Work Location: For most roles, employees are expected to work onsite on a regular basis at their designated office location. In‑office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.

Compensation: Requisition Compensation 155,000 to 209,000.

Benefits: As part of our comprehensive benefits package, Fannie Mae offers a broad range of health, life, voluntary lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well‑being.

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 to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form.