Global Commodity Data Scientist & Econometrics

Missouri Ag Connection; Chesterfield (MO); On-site; USD 100,000 - 150,000; Full time

Job summary

Bunge, a premier agribusiness solutions provider, seeks a Data Scientist to join the Economic Analysis team. You will apply advanced statistical modeling, econometrics, and ML to analyze vast internal and external datasets and forecast global commodity market dynamics.

Collaborate with economists, market analysts, data engineers, and traders to translate challenges into solvable analytics and deploy high-performance predictive models.

Qualifications

• MS degree in a quantitative field as listed
• Minimum 2 years in a data scientist or similar role
• Proficiency in Python for data analysis, ML, and visualization
• Strong SQL skills for data extraction and analysis
• Solid understanding of statistics, econometrics, and ML algorithms
• Excellent communication and presentation skills
• Detail oriented and collaborative in a global environment

Responsibilities

• Collaborate with economists, market analysts, data engineers, and leaders to translate challenges into solvable data science problems
• Translate business problems into analytics and deploy high-performance predictive models
• Design analytical strategies to extract insights from diverse data sources
• Monitor and refine model performance to ensure accuracy and impact
• Communicate findings and recommendations to senior leadership and traders to inform decisions

Skills

Python

SQL

Statistics

Econometrics

Machine Learning

Communication

Education

MS in Economics

MS in Agricultural Economics

MS in Statistics

MS in Computer Science

MS in Quantitative Finance

MS in Business Analytics

Tools

pandas

NumPy

scikit-learn

statsmodels

TensorFlow

SQL

Job description

Bunge, a premier agribusiness solutions provider, seeks a Data Scientist to join the Economic Analysis team. You will apply advanced statistical modeling, econometrics, and ML to analyze vast internal and external datasets and forecast global commodity market dynamics.

Collaborate with economists, market analysts, data engineers, and traders to translate challenges into solvable analytics and deploy high-performance predictive models.