Data Scientist
Navy Federal Credit Union
The Data Analytics and Reporting team at NFFG develops scalable analytics solutions that support investment strategy, member engagement, and business performance. This role involves building predictive models and applying mathematical optimization to improve targeting and decision-making. Responsibilities also include automating data pipelines and workflows, developing interactive dashboards, and producing recurring reports that deliver clear, actionable insights. Success in this role requires strong technical skills, business understanding, and the ability to communicate analytical findings effectively across teams
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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.
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.
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The Data Analytics and Reporting team at NFFG develops scalable analytics solutions that support investment strategy, member engagement, and business performance. This role involves building predictive models and applying mathematical optimization to improve targeting and decision-making. Responsibilities also include automating data pipelines and workflows, developing interactive dashboards, and producing recurring reports that deliver clear, actionable insights. Success in this role requires strong technical skills, business understanding, and the ability to communicate analytical findings effectively across teams
2-3 years of experience with requisite competencies
Proficient in Python, SQL, PySpark, Power BI (or Tableau)
Hands-on experience with statistics, machine learning, time series forecasting, and mathematical optimization
Strong communication, collaboration and presentation and problem-solving skills
Experience with cloud platforms (e.g., Azure Databricks)
Research skills
Independent judgment
Data storytelling and technical presentation skills
Problem solving and critical thinking
Bachelor's Degree in Computers Science, Engineering, Statistics, Operations Research, Mathematics, or degrees in similar quantitative fields
Desired Qualifications
- Master's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering
- 3+ years of experience with requisite competencies
Hours: Monday - Friday, 8:00AM - 4:30PM Hybrid
Location: 820 Follin Lane, Vienna, VA 22180
This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you.
Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.
Develop and deploy predictive models (classification, regression, clustering, time series) to support investment behavior analysis and member targeting.
Automate data pipelines and modeling workflows for scalable deployment across data channels.
Develop interactive dashboards to visualize key trends and model insights
Apply mathematical optimization to improve portfolio strategy, and campaign effectiveness.
Conduct deep-dive analyses on member behavior, transactions, and product adoption to guide data-driven decisions.
Collaborate with cross-functional teams to align analytics with business objectives.
Present findings clearly to technical and non-technical audiences
Model monitoring and documentation