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Summary

A Data Scientist with newly acquired skills an insatiable intellectual curiosity, and the ability to mine hidden gems located within large sets of structured, semi-structured and unstructured data. Combining applied statistics, mathematics and visualization to explore the hidden value in data.

Education

20132016

B.Sc

United States International University

Bachelor Of Science in Information Systems & Technology ( Forensic IT & Cybercrime )

Online Certifications

  •  Introduction to Data Science in Python
  • Machine Learning Nanodegree, Udacity
  • React Nanodegree, Udacity
  • Statistics Specialization with R (Probability, Inferential Statistics), Duke University, Coursera
    Data Science Bootcamp with Python & R, Udemy

Skills

TECHNICAL SKILLS
  • Programming: Python, R, JS, ReactJS, HTML, CSS
  • Frameworks: Scikit, Pandas, NLTK, JQuery, Git
  • Database Systems: MySQL, MongoDB (NoSQL)
  • IDEs: iPython Notebooks, R Studio, Eclipse

Portfolio/Projects

3-way polarity (positive, negative, neutral) classification system for tweets, without using NLTK's sentiment analysis engine.

  •  Python, NLP, Scikit-learn

VISUALIZE WEBSITE CLICK STREAM DATA

The project entails working on Hive and HIVEQL to analyze clickstream data of a website to increase conversion and revenue.

  • Analyze JSON data;Loading JSON format to Hive

CREATING CUSTOMER SEGMENTS

Analyzing customer spending data using Unsupervised Learning techniques for discovering internal structure, patterns and knowledge.

  • Python, Scikit-learn, PCA, Clustering