Consulting

GDP estimation for the city of Santiago de Cali

This project was requested by Municipal Planning Department (DAPM) in Cali, Colombia. I coordinated I group of 10+ people to estimate the gross domestic product and other macroeconomic accounts of the City of Santiago de Cali. Besides guiding the data collection, I employed R to transform raw input files to estimate accounts and produce the final deliverable. A publication using these data was released where I wrote some the chapters (view publication).

Predicting the risk of health insurance un-enrollment

This project was requested by a major health insurer in Colombia. The insurer was concerned about the high number of customers leaving their health insurance too early, representing a loss for the company. We used big data and machine learning algorithms to plow raw data and produce predictive models to determine wether users are likely abandon their insurance plan. Our models had an accuracy rate of 95%.

Analyzing productivity and injury risk of sugar cane croppers

This project was requested by the Association of Sugar Cane Farmers (ASOCAÑA, in Spanish). We produced descriptive reports on production and well-being of croppers that I personally coded-up in R. My code was able to use input to automatically produce written reports using statistics and graphs. We also used epidemiological models to estimate and predict injury risk.