Data Science Intern

Bunge•Chesterfield, MO

About The Position

The Data Science Intern will join Bunge’s Data Science team within Global Economic Analysis for Summer 2027 (May–August) in St. Louis, Missouri. The internship offers hands-on experience applying advanced data science and economic research to commercial decision-making and risk management in global agricultural markets. The intern will use modern cloud computing tools and statistical methods to analyze internal and external datasets and contribute to predictive models covering commodity market dynamics, including crop production, pricing trends, and customer behavior. The role also includes improving analytical and data pipelines and completing a significant project presented to the economic research team.

Requirements

  • Minimum MS degree in Ag-Economics, Economics, Data Science, Statistics, Computer Science, Finance, Engineering, or a closely related quantitative discipline.
  • Hands-on experience with Python and familiarity with analytical libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, or Seaborn.
  • Experience using Python for data manipulation, statistical analysis, machine learning, and data visualization.
  • Strong SQL skills for extracting, manipulating, and analyzing data from relational and non-relational databases.
  • Understanding of version control systems, particularly Git.
  • Proactive self-motivation and ability to work independently and deliver solutions in a fast-paced, collaborative environment.

Nice To Haves

  • Experience with geospatial data analysis and deep learning for statistical modeling.
  • Experience with big data technologies and cloud-based data platforms and products, such as Google Cloud Platform or AWS.
  • Knowledge of agricultural commodity markets, including grains, oilseeds, or biofuels, and/or agronomics.

Responsibilities

  • Collaborate on developing and refining predictive models for crop production forecasts, pricing trends, and customer behavior.
  • Enhance analytical and data pipelines, potentially designing and implementing optimizations using Python and cloud computing tools.
  • Undertake and deliver a significant analytical project related to the team's core objectives.
  • Present the completed project and findings to the economic research team.
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