You are here: Home / CABI People / Cambria Finegold
Cambria Finegold
Director of Data Science, Modelling and AI
Nosworthy Way, Wallingford, Oxfordshire, OX10 8DE, United Kingdom
About
As CABI’s Director of Data Science, Modelling and AI, I am responsible for the strategic direction and overall leadership of this scientific area. My work focuses on applying data science to support the Sustainable Development Goals, developing human-centred approaches to harnessing the power of data and frontier technologies in a way that’s grounded in the reality of agricultural communities in developing countries.
My geographic focus has been primarily in Latin America and Africa, and my academic background is a mix of social science, computer science, and geospatial analysis. I have a strong interest in human-centred design, complex systems, and interdisciplinary methods which bring together natural and social science.
I joined CABI in 2011 as a Project Development Officer, managed the Plantwise Knowledge Bank from 2012 – 2016, created CABI’s Digital Development theme and led it from 2016-2025, before setting up the Data Science, Modelling and AI area. Prior to joining CABI, I had worked for WorldFish Center (CGIAR) and Oxfam GB, working in a range of areas including rural livelihoods, nutrition, value chains and markets, geographic information systems, natural resource governance, and gender.
CABI centre: Wallingford
Over 140 staff are based at CABI’s corporate office in Wallingford, working in Publishing, Sales and Customer Service, IT, Marketing, Finance, Project Development and Digital Development.
Related projects
Global Burden of Crop Loss
Given the pressures of climate change and growing global population, losing less of the crops that have already been sown on land or under cultivation, presents an important opportunity to enhance food security. While there is increasing recognition of potential gains from curbing post-harvest losses and consumer food waste, pre-harvest losses remain poorly understood. The Global Burden of Crop Loss (GBCL) aims to fill this gap by providing trusted, data-driven metrics on crop loss across different regions and crops. By analysing global data, assessing the impact of pests and diseases, and leveraging advanced technology, GBCL aims to equip decision-makers with the insights they need to take evidence-based action. With a clearer picture of where, how, and why crop losses occur, policymakers, researchers, and investors will be better positioned to implement solutions that improve agricultural resilience and food security globally.
Start: 01/04/19 -End: 31/12/27

