Giorgia is a Researcher in Data Science at The Inclusion Initiative, where she is engaged in the Diversity and Productivity from Education to Work project. Her research will focus on investigating how diversity, inclusion, and productivity are interconnected, as well as developing methodological approaches to identify and measure their relationships. In specific, she will explore how machine learning can be employed for causal inference in a large dataset about firms’ diversity and profitability metrics.  

Giorgia completed her PhD in Environmental Economics at LSE. Her research  involved creating a new dataset about electrification in the United States using image and natural language processing, as well as examining the relationship between weather variability, access to electricity, and employment using causal inference methods on large micro datasets.  

During her studies, Giorgia was employed as a tutor and course developer at the Digital Skills Lab and LSE Data Analytics course. In these roles, she taught a comprehensive curriculum covering the basics of coding in Python, R, and SQL, as well as the implementation of data analysis and machine learning. 

Before her PhD, Giorgia was employed in the private and non-profit sector through various research positions. As a Research and Data Associate at NRGI, she was responsible for researching and developing a new index to track mining governance across countries and contributed to working papers on the economics of resource extraction. In her previous role as a Data Analyst for a private advertisement company, she worked on a team that utilized machine learning models on attention data.