Data Scientist (Marketing preferred)

Provide analytical insights and scalable data solutions that solve complex business problems and drive informed decision-making. Leverage programming, automated reporting, data infrastructure, business intelligence, and advanced analytics to translate data into actionable business recommendations.

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.

Provide analytical insights and scalable data solutions that solve complex business problems and drive informed decision-making. Leverage programming, automated reporting, data infrastructure, business intelligence, and advanced analytics to translate data into actionable business recommendations.

Qualifications

• Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields
• Strong experience solving complex business problems and translating analysis into actionable business recommendations and strategic insights.
• Deep understanding of data infrastructure, data modeling, data pipelines, excel and reporting automation, and data quality, with a focus on scalable analytics.
• Proven ability to design and build executive-facing dashboards, KPI reporting, and self-service analytics solutions using Power BI, Tableau, or similar tools to monitor paid media and marketing performance, trends, and key business metrics.
• Proven track record in analyzing paid and marketing data across channels to identify performance drivers, trends, and opportunities for optimization.
• Proven record of partnering with Marketing stakeholders to translate data into actionable insights that support campaign and investment decisions.
• Excellent stakeholder management and communication skills, with the ability to partner with business teams, gather requirements, and clearly communicate findings to leadership
• Advanced proficiency in SQL, Python, PySpark, and Databricks
• 2-3 years of experience in exploratory data analysis and statistics
• Strong data storytelling and visualization skills, with ability to translate complex data and analytical findings into clear actionable insights for non-technical stakeholders
• Proven Experience developing and optimizing automated reporting: dashboards, and visualizations in Tableau/Power BI/excels to communicate performance, trends, and business insights
• Programming, data modeling, simulation, and mathematics
• R, Hadoop, SAS, SPSS, Scala, AWS
• Model lifecycle execution
• Technical writing
• Data storytelling and technical presentation skills
• Research Skills
• Interpersonal Skills
• Model Development
• Communication
• Critical Thinking
• Collaborate and Build Relationships
• Initiative with sound judgement
• Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
• Problem Solving (Responds as problems and issues are identified)
• Desired Qualifications
• Master's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering
• Additional Information
• Hours: Monday - Friday, 8:00AM - 4:30PM
• Location: 820 Follin Lane, Vienna, VA 22180
• 5510 Heritage Oaks Drive, Pensacola, FL 32526

Responsibilities

• Design and build automated reporting, dashboards, and self-service analytics solutions that improve reporting efficiency and accessibility.
• Develop scalable data infrastructure, pipelines, data models, and automated workflows using tools such as Databricks, SQL, Python, and PySpark.
• Analyze complex business problems to identify trends, opportunities, and actionable recommendations that support business decisions.
• Create and maintain dashboards, KPIs, and reporting solutions using Power BI, Tableau, or similar visualization tools.
• Partner with business and technical stakeholders to translate business needs into analytical solutions and clearly communicate insights and recommendations.
• Design, develop, and evaluate basic/routine predictive models and algorithms with some complexity
• Analyze and interpret results with some complexity
• Limited judgment and discretion within defined procedures and practices
• Develop and code basic software programs, algorithms, and automated processes
• 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