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Big data professional with three years of experience working for a structuring data driven project, fraud model implementations and recommendation systems to financial institutions.  Highly skilled in Hadoop ecosystem and system analysis.

Work History

Jul 2016 Present

Data Scientist


    ● Bank data analysis and statistical models development

Sep 2015Jun 2016

Big Data Systems Engineer


    ● Big data fraud project analysis;

    ● Big data environment consultant. 

Jun 2014Sep 2015

Big Data Systems Analyst


    ● Hadoop ecosystem analysis and projects deployments;

    ● Strategical data driven project implementation.

Oct 2011Jun 2014

Production Analyst


    ● Production environment analysis (mainframe);

    ● Credit card business projects deployments(mainframe).

Apr 2010Oct 2011

I.T Intern


    ● Credit card business projects (mainframe);

    ● Mainframe automations.

Oct 2008Apr 2010

Support Analyst

SP Systems

    ● Unix server maintenance;

    ● User and I.T infrastructure support.



Big Data (Data Science) - MBA


Bachelor of Computer Information Systems 

Mackenzie University


Machine Learning
Hadoop Ecosystem

Yarn, Solr, Kafka, Hive, Oozie


Aug 2016Present

Distributed Machine Learning with Apache Spark

Berkeley University ( EDX )

Principles required to develop scalable machine learning pipelines using Apache Spark

July 2016Present

Developing Data Products

John Hopkins University (Coursera)

Creating data products using Shiny, R packages, and interactive graphics.
Statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.

July 2016Present

Practical Machine Learning

John Hopkins University (Coursera)

Components of building and applying prediction functions with an emphasis on practical applications

July 2016Present

Regression Models

John Hopkins University (Coursera)

Regression analysis, least squares and inference using regression models.
Special cases of the regression model, ANOVA and ANCOVA.
Analysis of residuals and variability

June 2016Present

Introduction to Apache Spark

Berkeley University ( EDX )

Apache Spark concepts, transformations, actions and distributed processing

May 2016Present

Statistical Inference

John Hopkins University (Coursera)

Fundamentals of inference in a practical approach

May 2016Present

Reproducible Research

John Hopkins University (Coursera)

Concepts and tools behind reporting modern data analyses in a reproducible manner

May 2016Present

Exploratory Data Analysis

John Hopkins University (Coursera)

Techniques for summarizing data, plotting systems in R and  multivariate statistical techniques used to visualize high-dimensional data.

May 2016Present

Getting and Cleaning Data

John Hopkins University (Coursera)

Techniques needed for collecting, cleaning and sharing scientific data

Apr 2016Present

R Programming

John Hopkins University (Coursera)

R programming and how to use R for effective data analysis.

Apr 2016Present

The Data Scientist's Toolbox

John Hopkins University (Coursera)

Overview of the data, questions, and tools that data analysts and data scientists work with.

Mar 2016Present

Data Science Associate (EMCDSA)


Full understanding of techniques and tools required for big data analytics and data science.

Mar 2014Mar 2019

LPI 101

Linux Professional Institute

Ability to perform maintenance tasks, install and configure a computer running Linux.

International Experiences

Canada (Montreal) - 3 months improving languages (English and French)

United States (various cities) - Knowing other cultures and ways of thinking 


Portuguese (Native)
English (Advanced)
French (Basic)