Data Engineer with a solid background in analytical modeling, natural language processing, and machine learning, specialized in data applications for underserved contexts such as low-resource languages and geospatial intelligence. She is skilled in building end-to-end data solutions — from processing pipelines to scalable machine learning deployments — leveraging Python, SQL/NoSQL, and cloud platforms including AWS and GCP, and is recognized for combining technical rigor with ethical data practices and a strong commitment to social impact.

At CentroGeo she led the development of a machine learning classifier for automatic language identification of Spanish and Yucatec Maya, and built multilingual data processing and translation pipelines to support research in language technologies. She is co-author of Detecting Indigenous Languages: A System for Maya Text Profiling and Machine Learning Classification Techniques (World Academy of Science, Engineering and Technology, 2024), and her team won 3rd place at the Yucatán i6 Datathon with “Red Ko’olel k’eex”, a web application addressing gender-based violence with a bilingual Spanish–Maya chatbot.