Navy Federal Credit Union

Our Digital Data Science Department is focused on building predictive solutions to support our mobile app and online banking operations. We develop tools that help business and app development teams enhance user experience and optimize performance.

We are seeking a motivated and talented year-round intern to join our growing team.

This role involves working with senior team members, department leaders, and business units to support research and development efforts using digital and financial data. You'll help explore new modeling ideas to enhance our data science products, generate insights into customer digital behavior, analyze mobile app and website usage trends, and examine customer sentiment. Familiarity with financial services and banking products is a plus, as it can support the design of predictive tools that help customers improve financial management and overall financial well-being.

This is a year-round, full- or part-time internship with flexible hours based on your academic schedule.

• Must be pursuing a degree from an accredited college/university
• Knowledge of statistics and data science use cases
• Programming abilities in SQL, Python, R, or similar languages in data exploration, data preparation, modeling, prediction, and statistical analysis
• Ability to learn and use data and cloud environments such as Azure and Databricks
• Technical writing skills
• Communication and data storytelling presentation skills of technical material
• Ability to collaborate and build relationships
• Effective organizational, planning and time management skills
• Ability to work independently and in a team environment

Desired Qualifications:

• Pursuing a degree in data science, statistics, mathematics, or degrees in similar quantitative fields
• Strong knowledge of statistics and machine learning techniques and tools including logistic regression, XGBoost, neural networks, NLP, and clustering
• Familiarity with task-tracking tools (ADO, ServiceNow, Asana, Jira, etc.)
• Perform research and analysis on emerging trends in mobile banking data science domains; may include quantitative and/or qualitative analysis
• Explore datasets and existing available technologies and tools
• Write code in Python and SQL to summarize and analyze data
• Analyze and interpret results with some complexity
• Combine knowledge of data science techniques with industry research on solutions in the mobile banking sector, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting
• Develop whitepapers and research summaries to help strategically target new model development initiatives
• Collaborate with team members and participate in team project planning
• Utilize effective written and verbal communication to document and present findings