Vicente Albíter is a quantitative researcher in MSCI’s factor-research team. He focuses on employing natural-language processing (NLP) and large-language models to extract financial signals from unstructured data and enhance interpretability of MSCI's factor-model data Previously, as a data scientist, Vicente researched various applications of Bayesian and geospatial machine-learning models in manufacturing, retail and public health. He holds an M.S. in computer science from IIMAS-UNAM and a B.S. in mechatronics engineering from UNAM.