Summer Associate Internship (Data Scientist)

Overview

The Credit Risk Strategy & Analysis team consists of analysts, modelers, and data scientists who develop analytical solutions and recommend strategies that support maximizing the net profitability of Lending portfolios while managing credit risk and serving members. This is done through the development of credit card line assignment and line increase strategies, pricing models for the consumer loan portfolio, and other analytical efforts.

The team is looking for a Data Scientist Summer Associate to participate in projects and efforts related to enhanced analytics tracking, model building, dashboarding, or automation.

Work includes but is not limited to:

• Providing independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization.
• Creating descriptive, predictive, and prescriptive models and insights to drive impact across the organization.

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

• Use modern technologies like Python, R, Scala, and Spark to analyze large data sets
• Provide insights and solutions to solve business problems
• Manage and analyze big data to build impactful data models
• Evaluate and improve model design and performance
• Collaborate with team members and stakeholders to deliver solutions
• Transform data into useful formats for decision-making
• Create visualizations and dashboards to monitor trends
• Conduct model validations and assess performance
• Create reports to assist with business planning and strategy
• Lead initiatives to streamline or automate processes
• Develop and refine strategies for underwriting, pricing, and/or portfolio monitoring

Qualifications

• Currently pursuing an undergraduate or graduate degree in Data Science, Statistics, Economics, Mathematics, Computer Science, Engineering, or another quantitative field
• Ability to understand complex business problems and define analytical solutions
• Coding experience with Python, R, Scala, or Spark as well as SQL
• Ability to manipulate raw data within visualization tools to create effective dashboards that communicate end-to-end data outcomes visually
• Proficiency in storytelling with data skills
• Strong verbal, interpersonal and written communication skills
• Familiarity using GitHub for documentation and code collaboration purposes
• Familiarity with Databricks
• Familiarity using Copilot or other AI agents to perform tasks

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