The Credit Risk Strategy & Analysis team needs to develop analytical solutions and recommend strategies that support maximizing the net profitability of Lending portfolios while managing credit risk and serving members. This involves developing credit card line assignment and line increase strategies, pricing models for the consumer loan portfolio, and other analytical efforts. The Data Scientist Summer Associate will contribute to enhanced analytics tracking, model building, dashboarding, or automation.
Requirements
- 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
- Familiarity using GitHub for documentation and code collaboration purposes
- Familiarity with Databricks
- Familiarity using Copilot or other AI agents to perform tasks
- Use modern technologies like Python, R, Scala, and Spark to analyze large data sets
- Evaluate and improve model design and performance
Responsibilities
- 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.
- 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
- Transform data into useful formats for decision-making
Other
- Ability to understand complex business problems and define analytical solutions
- Proficiency in storytelling with data skills
- Strong verbal, interpersonal and written communication skills
- Collaborate with team members and stakeholders to deliver solutions
- Currently pursuing an undergraduate or graduate degree in Data Science, Statistics, Economics, Mathematics, Computer Science, Engineering, or another quantitative field
