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John Deere

Builds farm, construction, and forestry machines

Data Science and Analytics Student Intern - Data and Analytics

Data ScienceConfirmed live in the last 24 hours
Internship$15 - $40 /hr

About the Job

Requirements

  • Graduate-level academic experience is preferred, including current enrollment in a Master's or PhD program in Data Science; others may apply.
  • Graduation date of Spring 2027 or later.
  • Available to work during the academic year for 16–20 hours weekly and during the summer semester for 30–40 hours weekly.
  • Must be registered as a full-time student at a U.S. or local accredited university or college.
  • Cumulative GPA of 3.0 or above.
  • Must be able to commute daily to the work location in Urbandale, Iowa, or Austin, Texas; relocation assistance is not provided.
  • Proficiency in Python, including experience with algorithms and data structures.
  • Proficiency in SQL.
  • Experience working with generative AI tools.
  • Foundational knowledge of machine learning and statistics.
  • Knowledge of big data analysis, including experience or coursework with distributed data processing frameworks such as Apache Spark.
  • Ability to create analytical outputs, dashboards, visualizations, or tools that help generate insights for customers and stakeholders.
  • Strong communication skills, including the ability to explain technical methods and findings clearly to technical and non-technical audiences.
  • High attention to detail and accuracy, and ability to manage work effectively.
  • Must be 18 years of age or older to apply.

Responsibilities

  • Explore analytical problems and develop data-driven solutions using data science, analytics, and artificial intelligence techniques.
  • Ingest, evaluate, clean, transform, and prepare structured and unstructured data for algorithms, models, dashboards, and analytical solutions.
  • Build analysis tools, prototypes, data pipelines, and dynamic visualizations to accelerate insight generation and support decision-making for internal customers and product teams.
  • Support the development and evaluation of algorithms, machine learning models, causal inference methods, and generative-AI-enabled workflows.
  • Research analytical, visualization, automation, and artificial intelligence methodologies in collaboration with data science, engineering, agronomy, user experience, and product subject matter experts.
  • Apply data science and statistical techniques to solve business and product problems across the product lifecycle.
  • Communicate findings, methodologies, assumptions, and recommendations to technical and non-technical stakeholders at multiple levels.
  • Work effectively in a collaborative, cross-functional environment while demonstrating curiosity, continuous learning, attention to detail, and high standards of quality.

Desired Qualifications

  • Experience designing, building, evaluating, or deploying agentic artificial intelligence systems, artificial intelligence assistants, workflow automation, or large language model-based applications.
  • Strong proficiency in causal inference, including experience with experimental design, quasi-experimental methods, treatment effect estimation, or causal modeling.
  • Experience with geospatial data science, including spatial analytics, geospatial feature engineering, remote sensing analysis, satellite imagery, or precision agriculture datasets.
  • Experience working with Databricks, Apache Spark, distributed computing, and large-scale data processing environments.
  • Experience building production-quality analytical workflows, reusable data products, or scalable data science pipelines.
  • Familiarity with cloud-based data platforms, model development environments, version control, and collaborative software development practices.
  • Experience working as part of a digital product team, including collaboration with product managers, engineers, designers, domain experts, and business stakeholders.
  • Ability to translate stakeholder needs into analytical questions, technical requirements, prototypes, and actionable insights.
  • Experience creating interactive dashboards, data applications, or visualization tools that support decision-making.
  • Knowledge of agricultural, geospatial, machine telemetry, Internet of Things, or digital product data is a plus.
  • Currently enrolled in a Master's or PhD program in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Agricultural Engineering, Geospatial Science, Remote Sensing, or a closely related technical field; candidates pursuing a Bachelor's degree may also be considered if they demonstrate exceptional technical ability, strong analytical skills, relevant project experience, and high potential for growth.
  • Coursework or research experience in data science, machine learning, causal inference, big data analytics, geospatial analytics, artificial intelligence, or software development.

About the Company

John Deere

Builds farm, construction, and forestry machines

John Deere builds tractors, combines, and other farm machines, along with equipment for construction, forestry, road building, and lawn care. Many of its machines use GPS guidance and cameras to steer themselves and spray only the weeds they detect, and farmers track each field and machine through its Operations Center app. Deere sells machines, replacement parts, and repair service through a worldwide network of independent dealers, which handle sales, servicing, and trade-ins in their local areas. Deere & Company was founded in 1837 by blacksmith John Deere, whose steel plow cut through sticky prairie soil, and is based in Moline, Illinois.

Company size
10,001+
Company stage
IPO
Headquarters
Moline, IL
Founded
1837

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