AI Data Analytics Intern - Summer 2026

AI Data Analytics Intern

Description and Requirements

We're looking for a passionate summer intern to join the product development tools and transformation team in the Lenovo's Infrastructure Solutions Group (ISG). In this role, you will work with business stakeholders to create AI-driven analytic solutions that drive decision making across the ISG development organization. You will work with data engineers and data analysts to design and build data pipelines to make data available to the broader audience including the TPM, engineers and business stakeholders. You will have an opportunity to drive efficiency improvement, process optimization through machine learning and AI.

Responsibilities:

• Collaborate with the team to design and build ISG development data repository to enable advanced analytics
• Identify opportunities for data quality improvement and work with tools and business team to drive the changes
• Build Qlik Sense and Power BI dashboard to deliver data analysis results to broader audience
• Conduct statistical inference analysis to help project managers to better understand current development status and identify problem area at an early stage
• Use gen-AI to prepare key engineer document
• Develop algorithms to drive decision making consistency and identify cost reduction opportunities

Basic Qualifications:

• College student major in Mathematics, Computer Science, Engineering, Statistics, or in a related field
• Experience with programming languages: Python, R
• Experience with dashboard development: Qlik Sense, Power BI or other visualization applications
• Experience in SQL
• This role is based on site at Lenovo Corporate, following a 3:2 hybrid schedule (3 days in the office, 2 days flexible/remote)
• Fulltime commitment of 40 hours per week, with flexibility in daily scheduling and accommodation for preplanned vacation time
• 8week summer internship program: Program Start Date: Monday, June 1, Program End Date: Friday, July 24

Preferred Experience:

• A successful history of manipulating, processing and extracting value from large disconnected datasets is preferred
• Strong expertise and hands-on experience in applying machine learning and AI models is preferred