Navy Federal Credit Union's Savings Products Data Science team needs to develop predictive modeling solutions to understand member behaviors and engagement with their products, aiming to drive product uptake and deepen understanding of member interactions with deposit products.
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.
- Support data science and machine-learning 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
- Students will work on impactful projects and meaningful work during their internship.
