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I have experience in different segments of industry, such as strategic 
 consulting, financial, telecommunications and technology. All these 
 experiences helped me to improve my statistical and analytical

Massachusetts Institute of Technology

Udacity

Universidade Estadual de Campinas

Kaplan University

Data Scientist

Rafael Meirelles

Wildlife Studios

I worked on the Deep Analytics team identifying and acting on opportunities to apply machine learning on different areas of the company to increase revenue and make processes more efficient. 
 
 Initiatives examples : 
 
 - NPS modeling : understand how the network variables affect the NPS score of the company and use them to predict the detractors. 
 
 - Click Attribution : Comprehend the customer journey step-by-step using a 
 Markov Chain approach 
 
 		 
 -Court Decisions : Predict the probability of a lost cause as well as the amount of the sentence involved in the legal case so Nextel can attempt to sign agreements when it makes sense 
 
 - Complains : Using variables linked to the use profile of the customers, identify cases of high complain probability and take action preventively 
 
 - Network degradation study : Comprehend the concepts of KQIs such as RTT, 
 Lost Packages and Retransmission rate. The study identified 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 
 
 At Nextel out team works consistently with tools like : 
 
 - 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 
 julho de 2016 - fevereiro de 2018 1 ano 8 meses 
 Campinas 
 I worked on the Machine Learning Team developing statistical models and data analysis to support decisions of several internal clients on Movile 
 I used tools like R, Python, Microsoft Excel and SQL to extract as much value as possible from data and improve results. 
 A few examples of Data Science projects that I worked are : Client 
 Segmentation RFM analysis, Churn probability Survival Analysis and ETA for delivery services Linear regression, XGboost, Deep Learning, KNN . 
 
 Telefônica Brasil 
 Senior Big Data Analyst 
 março de 2016 - julho de 2016 5 meses 
 São Paulo e Região, Brasil 
 Development of classification models Logistic regression, Decision tree and 
 Random Forest oriented for churn. 
 
 
 Manipulation of big data sets using SAS, Teradata SQL and R. 
 
 TIM Brasil 
 Geomarketing consultant 
 julho de 2015 - março de 2016 9 meses 
 São Paulo e Região, Brasil 
 Development of models focused on understand behaviour based on 
 geolocation and sociodemographic variables. The main focus was in cluster analysis to predict buying propensity in home broadband. 
 Softwares used : Sas Miner, R and Microsoft Excel 
 
 Value Partners 
 Intern 
 setembro de 2013 - dezembro de 2013 4 meses 
 São Paulo Area, Brazil 
 I worked as an intern providing support to the consultants in projects in different segments such as services, oil and gas and chemicals. 
 
 Itaú Unibanco

Nextel Brasil

São Paulo 
 I supported the financial planning team developing models that projected automobiles sales based on macro economical variables to help in the 
 projection of future costs and revenues .

Rafael Meirelles’s posts