Operations Data Automation Intern

Job Description

Operations Data Automation Intern | Lenovo

The Tone:
This is a hybrid internship at Lenovo, located on-site at Lenovo Corporate in North Carolina, United States. Lenovo is a global technology powerhouse building a full-stack portfolio of AI-enabled devices, infrastructure, software, solutions, and services. This role is crucial for improving operational efficiency by documenting manual workflows, analyzing process performance, and implementing repeatable automated solutions across the organization. The intern will play a direct part in fostering a smarter future by enhancing how data drives operations.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: Hybrid, North Carolina, United States

• Mission: Improve operational efficiency by analyzing processes, identifying automation opportunities, and implementing automated solutions.
• Tech Stack: Python

What You’ll Actually Do
• Process Mapping: Map and document current operational processes and tasks, clearly identifying manual workflows and handoffs.
• Automation Scripting: Develop and maintain reusable Python scripts to enable data preparation, validation, and repeatable analytical workflows.
• Tool Design: Design user-friendly tools and scalable processes to streamline recurring operational tasks and reduce manual dependency.
• Reporting & Dashboards: Develop and/or support recurring reports and dashboards to improve operational visibility and decision-making.
• Implementation Support: Support the implementation, testing, and documentation of process improvements and automation solutions.

The Must-Haves
• Background: Enrolled in a Bachelor’s or Master’s program, or graduated within the past 12 months, in a quantitative or technical field such as Business Analytics, MIS / Information Systems, Engineering, Computer Science, Data Science, or Statistics.
• Experience: Demonstrated experience using Python to work with data, including cleaning, validation, transformation, or task automation.
• Skills: Strong analytical skills with the ability to prepare and work with clean, well-structured datasets, coupled with the ability to map and document processes, identify manual steps, and propose efficiency or automation improvements.