JOB DESCRIPTION: Summary: This position is in support of a series of projects that analyze how African food systems have been changing and how climate has affected those food systems. The project includes both primary data collection and quantitative analysis. The analyst will first explore innovative means of using artificial intelligence to streamline workflows that can be time intensive. The analyst will evaluate the extent to which large language models can save time when digitizing crop production statistics. They will furthermore explore when using such tools produces inaccurate or incomplete results. Finally, the analyst will explore subnational patterns of crop production, yield, and extensification stagnation as a means of understanding how food systems are changing in Africa.

Background: Crop production statistics are fundamental to analyzing yield gaps

ackground: Crop production statistics are fundamental to analyzing yield gaps, production trends, and the effects of climate variability, climate extremes, and climate change on food systems, as well as knock-on effects of how changes in crop production influence food insecurity and health outcomes. Crop production data is also required to develop operational crop yield monitoring and forecasting systems that support early warning systems

Systematic collation of subnational crop production statistics is particularly important for Sub-Saharan Africa, which contains countries with some of the highest levels of food insecurity and greatest economic dependency on agriculture. The proposed project focuses on updating and analyzing the largest and most comprehensive collection of open-access subnational crop statistics for Sub-Saharan Africa to date.

Qualifications:

Understanding of food systems, statistical methods, and agricultural economics
Experience using large language models to digitize crop production statistics
Experience developing research questions, performing literature reviews and performing econometric analyses on tabular data
Preferred Qualifications:

Experience and understanding with climate variability and change
Experience understanding human dynamics in food systems

Data Consultant

Applicant Search LocationWorldwide

Position Code2025-A42-001

Application Deadline7/11/2025

JOB DESCRIPTION:

Summary:

This position is in support of a series of projects that analyze how African food systems have been changing and how climate has affected those food systems.  The project includes both primary data collection and quantitative analysis. The analyst will first explore innovative means of using artificial intelligence to streamline workflows that can be time intensive. The analyst will evaluate the extent to which large language models can save time when digitizing crop production statistics. They will furthermore explore when using such tools produces inaccurate or incomplete results. Finally, the analyst will explore subnational patterns of crop production, yield, and extensification stagnation as a means of understanding how food systems are changing in Africa.

Background:

Crop production statistics are fundamental to analyzing yield gaps, production trends, and the effects of climate variability, climate extremes, and climate change on food systems, as well as knock-on effects of how changes in crop production influence food insecurity and health outcomes. Crop production data is also required to develop operational crop yield monitoring and forecasting systems that support early warning systems

Systematic collation of subnational crop production statistics is particularly important for Sub-Saharan Africa, which contains countries with some of the highest levels of food insecurity and greatest economic dependency on agriculture. The proposed project focuses on updating and analyzing the largest and most comprehensive collection of open-access subnational crop statistics for Sub-Saharan Africa to date.

Qualifications:

• Understanding of food systems, statistical methods, and agricultural economics
• Experience working with STATA, QGIS, and Machine Learning
• Experience using large language models to digitize crop production statistics
• Experience developing research questions, performing literature reviews and performing econometric analyses on tabular data

Preferred Qualifications:

• Experience and understanding with climate variability and change
• Experience understanding human dynamics in food systems