Cristina is a recent MIT graduate with background in quantitative social science. Over the past five years Cristina has been involved in various experimental and quasi experimental research projects inside academia and as part of program evaluation work in the non-profit sector, most recently through the Abdul Latif Jameel Poverty Action Lab. During her studies at MIT, Cristina focused on political economy and quantitative methods, taking a strong interest in causal inference, statistical modeling and a career in data science. At NYC Data Science Academy, she used supervised machine learning algorithms and ensemble methods to predict the magnitude of insurance claim losses and built a collaborative filtering based movie recommendation system using Python and Spark.
