MDI

Summer Internship - Data Analytics

Job Locations US-NC-Hickory
Posted Date 13 hours ago(12/16/2025 8:25 PM)
Requisition ID
2025-131718
# of Openings
1
Category (Portal Searching)
Engineering
Default: Location : Address
5005 Alex Lee Blvd. (28601)

Overview

2026 Data Analytics Internship Program

 

As a Data Analytics Intern, you will help consolidate and analyze customer data from multiple platforms (CRM, Monday.com, Accounting, Customer Phone Book, Customer Sales Recap, and more).

You will support the development of a unified data visualization portal and may contribute to AI agent development for advanced analytics.

This internship offers hands-on experience in data integration, visualization, and real-world business applications of generative AI.

 

 

Responsibilities

Department Goals

  • Develop a portal or data repository that houses key data for all customers, including business info, store info, services deployed, fees, communications/follow-ups, and key metrics.
  • Consolidate fragmented customer data into a single, easy-to-access platform.
  • Support the development of AI-driven analytics to identify customer priorities, service gaps, and emerging opportunities.
  • Collaborate with internal resources to drive strategic priorities and operational efficiency.

Qualifications

Qualifications

  • Currently pursuing a degree or training in Data Analytics, Data Science, Business Intelligence, or a related field.
  • Exposure to large language models, generative AI, or equivalent certifications is a plus.
  • Experience or coursework in data visualization tools (e.g., Power BI, Tableau).
  • Strong analytical and problem-solving skills.
  • Proficiency in Microsoft Office applications (Excel, Teams, Outlook, Word, PowerPoint).
  • Ability to work independently and collaboratively in a team environment.
  • Excellent communication skills, both written and verbal.

Skills You Will Learn

  • AI agent development and its application in business analytics.
  • Benefits of data visualization for driving business outcomes.
  • Real-world business applications of generative AI and data science.
  • Data integration and management across multiple platforms.
  • How to present data-driven recommendations to stakeholders.
  • Collaboration across departments to achieve shared goals.

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