Summer Associate Internship (Data Scientist)

Overview

The Savings Products Data Science team leads the development of predictive modeling solutions and capabilities driving in-depth understanding of our members' behaviors and engagement with our products. The Summer Associate will help support the team's data science efforts by creating impactful models that will drive product take-up or further our understanding of how members engage with our deposit products. Products include certificates of deposits, money market accounts, checking accounts, IRAs, and ESAs.

Representative Projects:

• 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.

The Summer Associate Program is a 12-week internship program beginning in May 2026 and ending in August 2026. Students will work on impactful projects and meaningful work during their internship. To qualify for this position, applicants must be currently pursuing a degree from an accredited college or university and have an anticipated graduation date of December 2026 or later.

Responsibilities

• 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

Qualifications

• Currently pursuing an undergraduate or graduate degree in Data Science, Computer Science, Information Systems, Business Analytics, or other related degree
• Experience with Python (Pyspark)
• Experience with SQL
• Experience with or knowledge of cloud technologies (Microsoft Azure, Databricks)
• Experience with data visualization (PowerBI, Tableau)
• Excellent communication and presentation skills
• Experience working with ambiguity (ie, data/analytical efforts where there is no clear solution)
• Curious and energetic nature

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