spots where these indicators needed to improve, ploting all of them in maps KML and using them as features to explain events like churn and complains using XGboost and Shapley Value Tools : - Python/R as statistical tools using libraries like pandas, matplotlib, scikit, dplyr, ggplot and caret - XGBoost, Random Forest, Shapley Value, Logistic Regression, Time Series as algorithms for statistical modeling - SQL Impala/Hive in a data lake environment to data extraction Movile, Data Scientist, Jul 2016 ~ Feb 2018 I worked on the Machine Learning Team developing statistical models and data analysis to support decisions of several internal
A tiempo completo / Interesado en trabajar a distancia
Massachusetts Institute of Technology・
MicroMasters Statistics and Data Science