Overview This role in Fraud Analytics Data Science team is responsible for designing, evaluating, and maintaining advanced analytical and machine learning solutions to detect and prevent Identity Theft fraud. This role focuses on improving fraud detection effectiveness while minimizing false positives, operational friction, and member impact. The position requires strong analytical judgment, end-to-end ownership of complex analyses, and close collaboration with cross-functional partners. The role includes engagement with third-party fraud vendors, focused on analytical validation and model performance oversight. This role analyze complex datasets for fraud patterns, and collaborate with cross-functional teams and vendor to enhance fraud detection systems and communicate analytical insights to stakeholders and executive leadership. Principal-level candidates will also be considered.
Responsibilities - Lead development, evaluation, and enhancement of statistical and machine learning models used for fraud detection.
- Conduct deep - dive analyses on fraud trends, large - loss events, false positives, and operational drivers.
- Design and validate feature engineering approaches using transactional, behavioral, and operational data.
- Apply appropriate techniques for highly imbalanced datasets, including cost - sensitive modeling and anomaly detection.
- Translate analytical findings into clear, actionable recommendations.
- Conduct deep-dive analyses on fraud patterns
- Work with large-scale datasets, ensuring data quality, feature engineering and model interpretability
- Develop algorithms and automate processes in cloud environment
- Use modeling and trend analysis to analyze data
- Collaborate with team members and participate in team projects and initiatives
- Utilize effective written and verbal communication to document and present findings
Qualifications - 3-5 years of experience in exploratory data analysis and predictive modeling
- Solid foundation in statistics and machine learning techniques
- Experience working with highly imbalanced datasets
- Ability to communicate complex technical findings to non-technical stakeholders
- Strong programming skills in PySpark, Python, SQL
- Technical writing
- Data storytelling and technical presentation skills
- Model Development
- Communication
- Critical Thinking
- Collaborate and Build Relationships
- Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields
Desired Qualifications- PhD's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering
Hours: Monday - Friday, 8:00AM - 4:30PM
Location: 820 Follin Lane, Vienna, VA 22180
About Us Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks.
Our approach to careers is simple yet powerful: Make our mission your passion.
Fortune 100 Best Companies to Work For 2025
Yello and WayUp Top 100 Internship Programs
Computerworld Best Places to Work in IT
Newsweek Most Loved Workplaces
2025 PEOPLE Companies That Care
Newsweek Most Trustworthy Companies in America
Military Times 2025 Best for Vets Employers
Best Companies for Latinos to Work for 2025
Forbes 2025 America's Best Large Employers
Forbes 2025 America's Best Employers for New Grads
Forbes 2025 America's Best Employers for Tech Workers
2025 RippleMatch Campus Forward Award Winner for Overall Excellence
Military.com Top Military Spouse Employers 2025
2025 Handshake Early Talent Award
From Fortune . 2025 Fortune Media IP Limited. All rights reserved. Used under license. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of, Navy Federal Credit Union.
Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to age, race, sex, color, religion, national origin, disability, veteran status, pregnancy, sexual orientation, genetic information, gender identity or any other basis protected by applicable law.
Accommodations: If you need accommodation or assistance for a qualifying condition to complete the online application (or during any stage of the hiring process), you can contact Navy Federal's Medical Accommodations team at or by calling 1-. This team cannot provide any information on job postings or application status.
Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team's discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position. For additional details regarding compensation and benefits, review the Benefits page of the Navy Federal Career Site.
Protect Yourself from Job Scams: Navy Federal Credit Union jobs are posted on our career site, jobs.navyfederal.org and reputable job boards (e.g., LinkedIn, Indeed). We do not post jobs on social media marketplaces, messaging apps or unverified websites. We will never ask candidates for payment, bank details or personal financial information during the hiring process.
Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
Never miss an opportunity! Create an alert based on the job you applied for.