Intern, Internal Data Services for Digital Nexus

Job Description

Intern, Internal Data Services for Digital Nexus | KPMG

The Tone:
This is an internship at KPMG, which can be located in U.S. Remote, in-office, or at client sites depending on business needs. KPMG provides audit, tax, and advisory services to organizations across major industries, focusing on delivering results for clients while fostering a culture of individual development and inclusive excellence. This role is crucial for maintaining and enhancing the firm’s internal data infrastructure and driving innovation through data governance and the application of cutting-edge technologies like Large Language Models.

The TL;DR
• Role: Internship
• Location: U.S. Remote (or In-Office/Client Site)

• Team: Internal Data Services
• Mission: This person will contribute to the governance, management, and maintenance of internal data, while also implementing AI-powered solutions to enhance software development.
• Tech Stack: Python, MS Office applications (Excel, PowerPoint, Word, Outlook)

What You’ll Actually Do
• Data Governance: Perform tasks related to the governance, management, and maintenance of data, including standards development, metadata management, and reporting.
• Data Documentation & Analysis: Document data interfaces and data mappings, then analyze and interpret the data.
• Requirements Development: Develop and maintain clear business and technical requirements documentation to support data initiatives, solution design, and implementation.
• Operational Support: Support the Internal Data Services leadership team in the overall operations of the data organization and identify process improvement opportunities.
• AI Solution Implementation: Implement Large Language Model (LLM) powered solutions to accelerate the software development lifecycle, including automated coding generation, bug detection, and test case creation.

The Must-Haves
• Background: Must be enrolled in an accredited college or university, pursuing a Bachelor’s degree or higher in Computer Science, Data Science, Data Analytics, Data Engineering, Information Systems, Information and Data Science, Information Management, Business Analytics, or Cognitive Science (data focused).
• Experience: Experience with data sourcing, analysis, and integration, along with a strong programming foundation (Python preferred).
• Skills: Strong technical aptitude, critical thinking skills, proficiency in MS Office applications (Excel, PowerPoint, Word, Outlook), excellent communication, time management, and emerging leadership abilities.
• Bonus: Knowledge of AI and machine learning concepts, coupled with an interest in applying these techniques to data-driven and automation use cases.