Data Scientist


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Job Title: Data Scientist
Location: Chesterfield, MO, Midwest United States, USA

Company: Bunge
Industry Sector: Agribusiness
Industry Type: Input Retail, Cooperative and Related Crop Services
Job Type: Full Time

Job Description: A Day In The Life:

Leveraging our inherent market intelligence is a critical component to Bunge's success, particularly in the dynamic agricultural markets. This the reason why Bunge has one of the large economic analysis teams in the industry. Our analysis team is comprised of over 50 analysts world-wide who gather, analyze, supply and demand and other pertinent information. The global analysts work closely with global traders to help market develop market theses that drive the company's trading and risk decisions. The team covers global grains, oilseeds, biofuels, ocean freight and livestock.

What You'll Be Doing:

The Data Scientist will be an integral part of the Bunge Economic Analysis team, leveraging advanced statistical modeling, econometrics, and machine learning to analyze vast internal and external datasets. This role is crucial for developing sophisticated predictive models that inform our understanding and forecasting of global commodity market dynamics, including crop production, pricing trends, and customer behavior, thereby advancing our economic research functions worldwide.

  • Collaborate effectively within cross-functional teams, including economists, market analysts, data engineers, and business leaders, to translate complex business challenges into solvable data science problems.
  • Translate complex business problems into data-driven analytics and machine learning tasks, then design, develop, and swiftly deploy high-performance, resilient predictive models using a range of machine learning, statistical, and econometric techniques.
  • Design and implement advanced analytical strategies and algorithms to extract, analyze, and leverage diverse data sources. Critically assess the effectiveness, accuracy, and suitability of various data inputs for global economic models.
  • Rigorously monitor, evaluate, and refine the performance of deployed machine learning solutions to ensure sustained accuracy and measurable business impact.
  • Clearly and effectively communicate complex analytical findings, model insights, and strategic recommendations to diverse audiences, including senior leadership, traders, and business units, supporting informed decision-making and global risk management.


Skills/Experience Requirements:
  • Minimum MS degree in Economics, Agricultural Economics, Statistics, Computer Science, Quantitative Finance, Business Analytics, or a closely related quantitative field.
  • Minimum 2-year of professional experience in a Data Scientist or similar quantitative role, preferably within an economic analysis, commodity trading, financial services, or agribusiness environment.
  • Expert proficiency in Python (e.g., pandas, NumPy, scikit-learn, statsmodels, TensorFlow) for data manipulation, statistical analysis, machine learning, and data visualization.
  • Strong SQL skills for data extraction, manipulation, and analysis from relational and non-relational databases.
  • Solid understanding of statistical inference, econometric modeling (e.g., time series analysis, causal inference), and machine learning algorithms (e.g., regression, classification, clustering, tree-based models).
  • Demonstrated ability to frame complex problems, design analytical solutions, and extract meaningful insights from large datasets.
  • Excellent communication and presentation skills with the ability to explain complex concepts or methods in a precise and clear manner.
  • Detail-oriented, proactive, self-motivated, build work relationships, and able to work both independently and collaboratively in a fast-paced, dynamic global environment.
  • 5+ years of industry work experience in Data Science fields.
  • Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep learning for statistical modeling.
  • Experience with big data technologies and cloud-based data platforms and products (e.g., Google Cloud Platform, AWS).
  • Familiarity with MLOps practices for deploying, monitoring, and maintaining machine learning models in production.
  • Specific knowledge of agricultural commodity markets (e.g., grains, oilseeds, biofuels), agronomics, etc.


Benefits:
Health Benefits - Offering choices so you can enroll in medical, dental and vision to meet your individual needs 401(k) - Investing in your future with an automatic 5% company contribution AND matching up to 4% of your contributions.
Family Support - Supporting new and growing families by providing 6 weeks of 100% paid parental leave and fertility coverage.
Tuition Reimbursement - Contributing to your education by reimbursing $5,000 of tuition expenses annually.
Time Off - Providing generous PTO based on professional work experience
0 - 9 years: 25 days
10 - 19 years: 30 days
20+ years: 35 day

Bunge (NYSE: BG) is a world leader in sourcing, processing and supplying oilseed and grain products and ingredients. Founded in 1818, Bunge's expansive network feeds and fuels a growing world, creating sustainable products and opportunities for more than 70,000 farmers and the consumers they serve across the globe. The company is headquartered in St. Louis, Missouri and has 25,000 employees worldwide who stand behind more than 350 port terminals, oilseed processing plants, grain facilities, and food and ingredient production and packaging facilities around the world.

Bunge is an Equal Opportunity Employer. Veterans/Disabled

Nearest Major Market: St Louis
Job Segment: Agronomy, Sustainable Agriculture, Research Scientist, Agricultural, Statistics, Agriculture, Science, Data

To apply please click on APPLY TO THIS POSITION

Job Post Date: 10/19/25
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