Part-Time Student - Data Science & Analytics

Responsibilities

• Lead and support key analytics projects at the John Deere Technology Innovation Center (JDTIC)
• Utilize analytics techniques to clean, preprocess, explore, and analyze data sets
• Extract actionable insights for advanced automation and sensing projects
• Collaborate with cross-disciplinary teams and stakeholders to deliver data-driven solutions
• Present findings and translate results into professional reports and presentations

Requirements

• Currently pursuing a Bachelor's, Master's, or PhD in a quantitative field (e.g., Computer Science, Data Science, Engineering, Math, Statistics, or Operations Research)
• Registered as a full-time student at a U.S. accredited college or university
• Expected graduation date of Spring 2027 or later
• Minimum cumulative GPA of 2.8
• Working knowledge of Python and other programming languages
• Experience with data modeling and analyzing text or numerical data

Preferred Qualifications

• Graduate degree candidate
• Knowledge of machine learning, Bayesian statistics, AI, signal processing, or optimization
• Experience with complex data visualization methods
• Proficiency in tools such as PyTorch, Databricks, ArcGIS, Git, Jupyter Notebooks, or SQL
• Understanding of transformers, CNNs, or Large Language Models (LLMs)
• Domain knowledge in agriculture, agronomic sciences, soil science, or GIS

Benefits

• Highly competitive base pay ($15 - $40 hourly based on education and function)
• Flexible work arrangements
• Savings and retirement benefits (401K and Defined Benefit Pension)
• Healthcare benefits with company HSA contributions
• Tuition assistance and fitness subsidies
• Employee Purchase Plan and various discount programs

About the Company

John Deere is dedicated to ensuring there is enough food, fiber, and infrastructure for a rapidly growing global population. We invest heavily in people and technology, empowering the world's brightest minds to tackle the planet's biggest challenges through innovation in automation and sensing.