Navy Federal Credit Union is looking to develop predictive modeling solutions and capabilities to drive in-depth understanding of members' behaviors and engagement with their products, including certificates of deposits, money market accounts, checking accounts, IRAs, and ESAs.
Requirements
- Experience with Python (Pyspark)
- Experience with SQL
- Experience with or knowledge of cloud technologies (Microsoft Azure, Databricks)
- Experience with data visualization (PowerBI, Tableau)
Responsibilities
- Build a machine-learning propensity model that predicts the likelihood that an NFCU member will have excess deposits in checking and should establish recurring transfers into a money market.
- Perform complex analytical work on large data sets to better understand issues around member engagement and member behavior.
- Support feature engineering work by creating or adjusting flags and/or aggregate data which will be used for future modeling efforts.
- Retrieve, analyze, and model data within our Azure Databricks environment
- Package results and findings into executive-level presentation and present to senior management
Other
- Currently pursuing an undergraduate or graduate degree in Data Science, Computer Science, Information Systems, Business Analytics, or other related degree
- Excellent communication and presentation skills
- Experience working with ambiguity (ie, data/analytical efforts where there is no clear solution)
- Curious and energetic nature
- Anticipated graduation date of December 2026 or later
