Searcher
Tomasa Rodrigo
Tomasa Rodrigo
BBVA Research - Lead Economist

Tomasa Rodrigo is currently Lead Economist at BBVA Research in charge of Big Data projects for economic, social and geopolitical analysis. She has a large experience working with cloud infrastructures, large databases of a financial and social nature (media and social networks). She has published several articles about tracking geopolitical, social and economic events with Big Data and has been mentioned in well-known blogs like O’Reilly or Forbes.

She has a degree in Economics from the University of Granada (Summa Cum Laude), where she worked as research assistant for two years. She has a Master in Economic Analysis at the Carlos III University of Madrid (Thesis Score: 10/10) and she worked as a teacher of Econometrics during a year. She also has a master in Big Data provided by IBM.

She has published in academic journals as Eurasian Journal of Social Science and has worked in newspapers and magazines like El Pais and Cataluña Económica. She has presented in important forums of Data Science such as Central Banks, Big Data Spain, Machine Learning Spain and Google Cloud Summit.

She has also been an associate professor in Carlos III University and taught in several masters about Data Science and the use of Big Data.

Latest publications

We analyze the evolution of the semiconductor industry with the use of Big Data from global news databases (from GDELT) and NLP tecniques for sentiment analysis. By complementing with Google Trends and other BBVA Research geopolitical indicators, we analyze the main actors and components of the industry evolution.
The BBVA Research geopolitical monitor gathers real-time geopolitical indicators constructed from news processed with NLP, which allow for monitoring the media reaction to geopolitical and social events. This note has been published in the European Money and Finance Forum (SUERF).
Presentation for the Conference on Real-Time Data Analysis, Methods, and Applications hosted by Bank of Spain. We apply National accounting principles to obtain real-time, high-frequency Big Data consumption indicators with many applications.