Tell us more about your role and how do you apply data science to your projects

Data science is both a method and a core subject of my research. I use data science tools such as R and Python for data collection and analysis, as well as AI-based methods for data analysis. In addition, a central strand of my research agenda examines how policymakers themselves use data science tools, particularly AI. Since 2023, I have co-led a research project on the use of data science and AI by local policymakers in England. This project aims to understand how local officers interact with data and AI while helping them streamline data science processes in policymaking.

Is there a project from this past year that you are most proud of? 

I am particularly proud of my first postdoc project, in which I investigated the political connections of government officers in Brazil. In this project, I used R for the first time to merge large datasets on partisan affiliations that were too big for Excel to handle. I also used Python code to web-scrape information from official government documents online. Although I did not develop the code myself, this was my first practical use of data science to overcome concrete research challenges and it motivated me to join the PyLadies community, which supports women in developing Python skills. The project resulted in several publications, new methodological insights, and an original dataset on Brazilian government officers, containing unprecedented information extracted from official documents

What do you like most about being a DSC member? 

I appreciate the training and networking opportunities the DSC offers. Connecting with other researchers who use data science tools across different disciplines creates excellent possibilities for collaboration.

What is your favourite data science method? 

Social Network Analysis and Machine Learning are my favourite methods.

Are you camp Python/R/or something else?

Many data scientists tend to pick a side, but I am a committed fan of both R and Python. R was my entry point into data science, so I’m somewhat emotionally attached to it, while Python has become indispensable for several research tasks.