Principal Data Scientist
Job in
Vienna, Wood County, West Virginia, 22184, USA
Listed on 2026-10-30
Listing for:
Navy Federal Credit Union
Full Time
position Listed on 2026-10-30
Job specializations:
-
IT/Tech
Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Data Scientist
Location:
Vienna, VA, United States Workplace:
Hybrid
Schedule:
Full time, Regular Hours Posted:
Closes:
Targeted Salary Range: $131,800 - $181,200 annually
Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization. Understand business needs and identify opportunities for new products, services, and process optimization to meet business objectives through the use of cutting-edge data science. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization.
Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Mentor lower level staff.
Qualifications6+ years of experience with requisite competencies
Complete knowledge and full understanding of specialization
Statistics, machine learning , data mining, data auditing, aggregation, reconciliation, and visualization
Programming, data modeling, simulation, and advanced mathematics SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWSModel lifecycle execution
Technical writing
Data storytelling and technical presentation skills
Research Skills Interpersonal Skills Advanced knowledge of procedures, instructions and validation techniques
Model Development Communication Critical Thinking Collaborate and Build Relationships Initiative with sound judgement
Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)Independent Judgment Problem Solving (Identifies the constraints and risks)
Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields
Desired Qualifications Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering6+ years of experience applying advanced analytics, machine learning, and statistical methods to solve complex business problems and influence strategic decisions. Strong understanding of the end-to-end data science lifecycle, including data quality assessment, feature engineering, model development, validation, deployment, monitoring, and governance. Expertise in Voice of the Member, customer feedback, survey, complaint, contact center, or digital interaction data, with the ability to turn unstructured feedback into actionable insights.
Experience applying Natural Language Processing (NLP), text analytics, sentiment analysis, topic modeling, and/or Large Language Models (LLMs) to understand customer needs, behaviors, and experiences. Additional Information
Hours:
Monday - Friday, 8:00AM - 4:30PM EST
Location:
820 Follin Lane, Vienna, VA 22180
Responsibilities Design, develop, and evaluate large and complex predictive models and advanced algorithms Test hypotheses/models, analyze, and interpret results
Develop actionable insights and recommendations
Develop and code complex software programs, algorithms, and automated processes
Use evaluation, judgment, and interpretation to select right course of action
Work on problems of diverse scope where analysis of information requires evaluation of identifiable factors
Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets
Transform data into charts, tables, or format that aids effective decision making
Utilize effective written and verbal communication to document analyses and present findings analyses to a diverse audience of stakeholders Develop and maintain strong working relationships with team members, subject matter experts, and leaders
Lead moderate to large projects and initiatives
Model best practices…
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