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# Part-Time Student - Data Science and Analytics - Austin, TX or Urbandale, IA

- **Company:** Deere & Company
- **Location:** Austin, TX, United States
- **Salary:** $31,200.0 - $83,200.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Data Analysis, Databases, Github, Integrated Development Environments, Python (Programming Language), Machine Learning, SQL Databases, Unstructured Data, Deep Learning, Information Technology, Data Analytics, Databricks
- **Published:** August 9, 2026
- **Apply:** https://www.wayup.com/i-Machinery-j-Part-Time-Student-Data-Science-and-Analytics-Austin-TX-or-Urbandale-IA-John-Deere-641122494351072/

## About the Role

The Part-Time Student Program is primarily designed to augment the Company's regular full-time staff and is for students who work in parallel to their school schedule YEAR-ROUND., + Pursuing a Bachelor's, Master's, or PhD Degree in Agriculture, Computer Science, Data Analytics, Data Science, Engineering, Math, Statistics, or a related quantitative field; others may apply

 + Must be registered as a full-time student at a U.S. accredited college/university
 + Graduation date of December 2027 or later
 + Cumulative GPA of 3.0 or above
 + Available to work during the academic year 16-20 hours/weekly during the business hours of 6 AM to 6 PM
 + Available to work during the summer semester 32-40 hours/weekly during the business hours of 6 AM to 6 PM
 + Proficient with Python and SQL
 + Knowledge of applied operations research/machine learning/deep learning techniques
 + Ability to work with structured/unstructured data
 + Knowledge of working with AI tools for coding
 + Knowledge of Gurobi, GitHub, VSCode, Databricks
 + Committed to working in an Agile environment
 + Must be able to commute to the work location in Austin, TX or Urbandale IA on a regular basis
What Makes You Stand Out

 + Domain knowledge in Crop Science, Soil Science, or Agronomics
 + Applied knowledge of OR algorithms
 + Pursuing a PHD in Industrial Engineering/Operation Research, Computer Science, Data Science

## Description

As a Part Time Student - Data Science and Analytics for Deere & Company World Headquarters located in Austin TX or Urbandale IA , you will:

 + Lead and/or support key analytics projects as a part of John Deere's Intelligent Solutions Group.
 + Utilize analytics techniques to clean, preprocess, explore, and analyze data sets and extract actionable insights for advanced sensing projects
 + Collaborate in a fun, friendly, and fast-paced team environment across disciplines and with key stakeholders to deliver data-driven solutions for the business
 + Present your findings in meetings and translate your results into reports and presentations
This position is not available to students on immigration visas, The terms of the applicable benefit plans, and all company actions administering or interpreting these plans, continue to control. Deere & Company reserves the right to suspend, amend, modify, or terminate the Plan(s) in any manner at any time, including the right to modify or eliminate any cost-sharing between the company and participants. Changes, which can be made at any time, are made by action of the company's board of directors, or to the extent authorized by resolution of its board of directors, or by the Deere & Company Compensation Committee. In the event of a conflict between the language of the official Plan Documents and this document, the language of the official Plan Documents will control.
ACA Section 1557 Nondiscrimination Notice
The John Deere Health Benefit Plans for Salaried Employees and The John Deere Benefit Plan for Wage Employees comply with applicable Federal civil rights laws and do not discriminate on the basis of race, religion, color, national origin, sex, age, sexual orientation, gender identity or expression, status as a protected veteran, or status as a qualified individual with disability.
Nearest Major Market: Austin Job Segment: Computer Science, Agricultural, Industrial Engineer, Database, Agronomy, Technology, Agriculture, Engineering


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