Process Automation

About the Role

Part-Time Student - Process Automation for John Deere Power Products located in Greeneville, TN. This role supports the Greeneville factory by applying data engineering, advanced analytics, automation, optimization, and emerging AI technologies to practical manufacturing and material-flow challenges. The student will work with operations and technical stakeholders to convert data and business needs into repeatable tools, decision-support solutions, and measurable process improvements.

Key Responsibilities

• Explore manufacturing, logistics, and material-flow problems and translate them into clearly defined analytics or automation projects.
• Build, improve, and maintain data pipelines that ingest, clean, validate, combine, and prepare information from multiple sources.
• Develop interactive dashboards, KPI reporting, and self-service analytical tools that improve visibility and speed decision-making.
• Prototype predictive, prescriptive, or machine-learning solutions for use cases such as material movement, capacity, inventory, quality, safety, maintenance, and workflow optimization.
• Create process automations and lightweight applications that reduce repetitive manual effort and improve data consistency.
• Integrate databases, enterprise systems, files, and APIs into dependable analytical workflows while maintaining source traceability.
• Apply simulation, optimization, geospatial analysis, or digital-twin concepts where they provide practical value to factory operations.
• Document requirements, data logic, model assumptions, testing, and user guidance so solutions can be supported and scaled.
• Present findings, methods, risks, and recommendations in clear language to both technical and non-technical stakeholders.
• Partner with users to test solutions, gather feedback, troubleshoot issues, and support adoption.

Examples of Potential Assignments include developing visibility dashboards, automating data workflows, prototyping optimization models, building AI-assisted knowledge tools, creating geospatial views, and evaluating model performance.

Requirements & Tech Stack

• Currently pursuing a bachelor’s, master’s, or doctoral degree in Industrial Engineering, Computer Science, Data Science, Business Analytics, Information Systems, or a related technical field.
• Registered as a full-time student at an accredited college or university, with the ability to work year-round in parallel with the academic schedule.
• Cumulative GPA of 2.8 or above.
• Graduation date of Spring 2027 or later.
• Ability to work approximately 10-20 hours per week during the academic year and up to 35-40 hours per week during the summer.
• Ability to commute to the Greeneville, Tennessee work location.
• Hands-on programming or analytical experience using Python, SQL, R, Scala, or a comparable language.
• Experience organizing, transforming, validating, and analyzing data from multiple sources.
• Experience developing dashboards, analytical applications, or reporting tools.
• Ability to explain technical work clearly, document solutions, and collaborate with non-technical users.
• Strong problem-solving skills, intellectual curiosity, and the ability to work independently while seeking input when needed.

Qualifications (What Makes You Stand Out)

• Experience with machine learning, predictive modeling, explainable AI, computer vision, natural-language processing, Retrieval-Augmented Generation, or agentic AI workflows.
• Experience with data engineering technologies such as ETL/ELT, Spark or PySpark, Databricks, Fabric, data warehouses/lakehouses, batch processing, or real-time streaming.
• Experience with Power BI, Tableau, Microsoft Power Platform, Streamlit, Dash, or similar visualization and application-development tools.
• Experience integrating REST APIs, relational databases, cloud services, or enterprise systems into analytical solutions.
• Experience with operations research, linear or network optimization, simulation, routing, digital twins, or graph-based analytics.
• Experience with Git, CI/CD, Docker, cloud platforms, or structured software-development practices.
• Knowledge of manufacturing, warehousing, logistics, supply chain, material flow, or industrial operations.
• Experience delivering a technical project from problem definition through deployment, user testing, documentation, and handoff.