A DAY IN THE LIFE:

The Data Scientist will be part of Bunge Food Solutions within the Data Center of Excellence (COE) team. This position is responsible for developing advanced analytics solutions, leveraging machine learning models, and extracting actionable insights from complex datasets to optimize operations, report on business performance gaps, and identify growth opportunities for the commercial decision makers.
This role serves as a catalyst for transforming raw data into actionable intelligence sustainably, enabling stakeholders across commercial functions make informed decision that improve business performance; identify potential challenges and solution to address those challenges. Thus, this role will collaborate with cross-functional teams to ensure the effective integration of data analytics into business strategies to deliver measurable value and innovation in a dynamic, sustainability-focused industry.

TRAINING AND KNOWLEDGE SHARE

• Purpose: Foster a culture of data literacy, process ideation, and system efficiencies, empowering stakeholders to leverage data and systems to increase efficiencies.
• Activities: Provide training and support to stakeholders/team members on tools, dashboards, report, and systems. Share best practices, tips, and insights through workshops, documentation, and knowledge sharing sessions.

SKILLS/EXPERIENCE REQUIREMENTS:

• Master’s degree in computer science, statistics, economics, agribusiness, mathematics, finance, or related field required. PHD Preferred
• Minimum 2-year experience in a data scientist position or 3-5 years in analyst position, with evidence of analytical contribution, preferably agribusiness or business systems background.

In the realm of our Bunge Food Solutions business, some of the more challenging aspects often revolve around handling large, convoluted datasets with varying degrees of accuracy/quality, adequacy, and completeness. Understanding the business processes is another critical pre-requisite to understand how the data is created and used. Additionally, navigating through complex relationships within the data and identifying meaningful patterns or insights can be a daunting task.