About the role#
This is a paid, part-time internship for the Summer 2026 term. You will work on-site at either our Austin, Texas, or Urbandale, Iowa, office. This role is open to students pursuing degrees in Data Science, Statistics, Mathematics, Computer Science, Business Administration, Economics, Finance, or Operations Management.
What you'll do#
- Assist with data collection and management tasks.
- Support the team in analyzing data trends.
- Create visualizations to present data findings.
- Contribute to reports that summarize data insights.
- Perform statistical analysis to support project goals.
What you'll need#
- Proficiency in programming languages like Python or R.
- Experience using data analysis tools.
- Knowledge of statistical methods.
- Strong mathematical skills.
- Ability to work effectively in a team environment.
Location & details#
- Locations: Austin, Texas or Urbandale, Iowa.
- Work modality: On-site.
- Term: Summer 2026.
- Sponsorship: Not available.
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.
