Data Software

VIJAYAKUMAR CHOKKALINGAM – RESUME

**** *** **** **** #***, Houston, TX 77058 832-***-**** ********@*****.***

EDUCATION

Master of Science in Computer Science and Engineering Aug 2016

University of Houston Clear Lake, Houston, TX GPA: 3.330

Achievements: Received Graduate Teaching Assistant scholarship and worked as TA for a course for 8 months

Bachelor of Technology in Information Technology April 2011

Sri Venkateswara College of Engineering, Chennai, IND GPA: 3.400

CERTIFICATIONS

Data Science Specialization by John Hopkins University (2016)

oR Programming, Statistical Reference, Regression Models, Practical Machine Learning, Getting and Cleaning Data, Exploratory Data Analysis, Reproducible Research, Developing Data Products

Other Courses: Probability and Statistics, Discrete Mathematics, Web Development, Software Process, Object Oriented Programming, Requirement Engineering, Data Structures, Software Architecture

SAS Advanced Program for SAS 9 (2016)

SAS Base Program for SAS 9 (2016)

ITIL Foundation Certification in IT Service Management (2013)

SKILLS

Statistical Packages: R, R-Studio, SAS, MS Excel, VBA/Macro, python Notebook, Jupiter

Computer Languages: Python, HTML, CSS, C++, Java Databases: MySQL, Oracle, SQL Server, Hive

Visualization Packages: Tableau, ggplot2, Shiny, googleVis, RCharts, R-Markdown.

Other Tools: Talend, Pentaho, Crystal reports, Tivoli Workload Scheduler(TWS), ControlM

RELEVANT WORK EXPERIENCE

Data Analyst Consultant, Cognizant Technology Solutions, IND Jun 2011 – Dec 2014

Forecast channel revenue by leveraging linear regression and validated results with online projected revenue.

Conducted data processing/manipulation, data cleansing, statistical modeling, programming and analysis work on customer behavior and relationship projects using SAS, Python and SQL.

Developed ad-hoc reports/metrics, dashboards and scorecards to support business operations in decision making

Conducted QA test of an ROI optimization and projection tool by testing and cross-validating different scenarios.

RELEVANT PROJECTS

Telecom User Churn Analysis Jun 2016

Used regression model to do churn analysis for telecom subscription using data of 10000 users & 100 features.

Used Variable Influence Measure to select the most important variables and also removed high collinear variables.

Choose the best performing model by looking at Lorenz Curve, Lift Charts, Gain Charts and Gain Value for models.

Predict Survival on the Titanic May 2016

Done extensive data cleaning by performing exploratory analysis to understand dependency among feature.

Used ridge regression for feature selection and developed a multinomial model and random forest model.

Developed algorithm in various statistical environments namely R, Python and SAS to compare the model results.

IMDB Users Segmentation using Ratings Mar 2016

Linked the given movie data and external IMDB API’s to increase the feature sets for the data.

Preliminary developed a Hierarchal Clustering to determine the optimal number of clusters for the Users.

Developed a K-means clustering using the optimal clusters from hierarchal to develop a classification algorithm.

Twitter US Airline Sentiment Analysis Jan 2016

Analysed 300000 tweets of the user’s sentiments regarding the US Airlines for the month of February 2015.

Developed a classification algorithm using the data that would classify tweets as positive, negative and neutral.

DevOps for Continuous Software Delivery and Infrastructure change Jan 2016

Published a paper on how DevOps can be used efficiently for the design and implementation of the software.

Understood the core concepts of DevOps and its principles namely, infrastructure-as-code, continuous deployment, automation, monitoring, and security.

Software Driven Special Design Vehicle for Physically Challenged May 2015

Analysis of the design of Software driven Vehicle for physically challenged.

Used fact finding techniques like Interview, brainstorming, surveys to gather requirements from the users in real time to perform the analysis; Identified key functional and non-functional requirements.

Performed validation and verification of the requirements and came out with desired requirements in a report.

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