Economist with minor in finance and Master in Economics from Universidad de los Andes.

She has served as assistant professor of the subject “Data Mining and its Applications” of the master’s program of the Faculty of Economics of the Universidad de los Andes and assistant professor of the summer courses “Machine Learning and Public Policy” and “Econometrics and Machine Learning ”. He has also been a research assistant at the science faculty of the same university.

He has experience in the use of machine learning techniques to solve various problems of a predictive nature in the financial, health, education and energy sectors, as well as in the application of econometric techniques. In particular, his experience covers the implementation of predictive models for the diagnosis and progression of chronic diseases, predictive models for the academic performance of students, predictive models for clients at risk of non-compliance, prediction of macroeconomic series, systems for the detection of anomalies and credit risk and money laundering and terrorist financing systems (SARC and SARLAFT). From the economics side, her experience focuses on health economics and impact evaluation.

Her areas of interest focus on predictive models using machine learning techniques, causal inference, and the intersection between the two areas.