About the role#
This is a paid, part-time internship for the Summer 2026 term. Students will work on-site to support data-driven projects within the machinery manufacturing industry.
What you'll do#
- Assist in the collection and management of data.
- Support the analysis of data trends and perform statistical analysis.
- Create visualizations to represent data findings.
- Contribute to reports detailing data insights.
What you'll need#
- Current enrollment in a degree program related to Data Science, Statistics, Mathematics, Computer Science, Business Administration, Economics, Finance, or Operations Management.
- Experience with data analysis tools and knowledge of statistical methods.
- Proficiency in programming languages such as Python or R.
- Strong mathematical skills.
- Ability to work effectively in a team environment.
Location & details#
- This position is based on-site in either Austin, Texas, or Urbandale, Iowa.
- This role does not offer sponsorship.
About John Deere
John Deere manufactures machinery for agriculture, construction, forestry, and turf care. The company operates globally with a focus on equipment and technology for food, fuel, and infrastructure production. Founded in 1837, the firm maintains its headquarters in Moline, Illinois. It functions as a public company with over 55,000 employees.
How to get in at John Deere
Applying early gives you a distinct advantage at John Deere because recruiters review applications before the pile grows too large. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you can submit your materials among the first. This helps you avoid the common frustration of being lost in a massive applicant pool. Reaching out to the right person often yields better results than submitting to a general queue. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the position or a referral. This direct approach materially improves your response rates compared to standard methods.
