Data Scientist Intern

CorpayAtlanta, GA
Onsite

About The Position

Looking for a summer internship with a highly dynamic, entrepreneurial company? Seeking a rewarding summer experience that will stand out from the crowd? Corpay is a leading global payments and financial services firm headquartered in Atlanta, GA. We invite you to join our 8-10 week paid summer internship program for rising juniors and seniors.How We Work As an intern you will be expected to work in an in-office environment. Corpay will set you up for success by providing: Assigned workspace in office our Buckhead office location Company-issued equipment Formal, hands-on training

Requirements

  • Currently enrolled in an accredited Bachelor’s or Graduate degree program in Data Science, Statistics, Computer Science, Economics, or a related quantitative field; rising junior or senior preferred.
  • Strong academic record with a GPA of 3.5 or higher.
  • Proficiency in Python or R (e.g., pandas, scikit-learn) and SQL; familiarity with data analysis, statistical methods, and basic machine learning concepts.
  • Strong written, verbal, analytical, and interpersonal skills, with the ability to communicate insights effectively to both technical and non-technical audiences.
  • Demonstrates maturity, professionalism, and a proactive, problem-solving mindset.
  • Must be able to commit to a full-time schedule (40 hours/week) for 10–12 weeks during the summer internship period.

Nice To Haves

  • Exposure to AI/ML techniques, including experience or interest in working with large language models (LLMs), text analysis, or data-driven automation is a plus.
  • Experience in cloud environments like AWS, Aruze.

Responsibilities

  • Performing exploratory data analysis to uncover trends and patterns, and applying statistical and machine learning techniques to support use cases such as customer segmentation, lead prioritization, and revenue optimization.
  • Developing and evaluating predictive models and AI-driven solutions, including leveraging large language models (LLMs).
  • Cleaning, transforming, and integrating data from multiple sources to ensure high-quality inputs for analysis and modeling.
  • Building AI agents and visualizations to communicate insights clearly to stakeholders and support business decision-making.
  • Collaborating with cross-functional teams to translate business problems into data science and AI solutions, and iterating based on feedback and performance.
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