Software Engineer

Arati Jairam Bhat

312-***-**** ***********@*****.*** https://www.linkedin.com/in/aratibhat/

SUMMARY

Seeking a position in Information Technology with a progressive organization, providing an opportunity for growth and advancement where I can utilize my education and professional work experience EDUCATION

ILLINOIS INSTITUTE OF TECHNOLOGY (Chicago, Illinois) Aug 2016-May2018 Master’s in Computer Science (GPA: 3.2/4)

● Volunteered for International Student Check-In Coordinators, Help-A-Hawk Aug 2017-Aug 2017

● Courses: Data Preparation and Analysis, Advanced Data Mining, Machine Learning, Online Social Network Analysis, Enterprise web application, Advanced Database Organization

VISVESVARAYA TECHNOLOGICAL UNIVERSITY (Karnataka, India) Aug 2009-May 2013 Bachelor of Engineering in Computer Science (GPA: 3.5/4)

● Courses: Java, Data Structures, Design and Analysis of Algorithm, Object Oriented Programming, Database Management Systems, Software Testing

SKILLS

● LANGUAGES: Java, JavaScript, HTML, CSS, R, Python, SQL, XML, VB script, Sencha ExtJS, C, C++

● TOOLS: Selenium WebDriver, Appium, SeeTest Automation tool, Eclipse, HPE QTP, UFT with Perfecto Mobile Plug-In, Google Analytics, Atlassian JIRA, Zephyr for JIRA, Atlassian Confluence, Microsoft Visio, Visual Studio, MySQL, Bitbucket, GitHub, SQLite

● CERTIFICATIONS: Experitest SeeTest Automation, Cloud and Manual tool PROFESSIONAL EXPERIENCE

Mphasis (Bangalore, India) Aug 2013-Jul 2016

Software Engineer

● Extensive experience working on manual testing and automating test scripts for Mobile and Web applications

● Experience in scripting mobile test automation tools - Selenium WebDriver, Appium, HPE QTP, HP UFT with Perfecto Mobile Plug-In, Experitest SeeTest automation

● Worked on writing about 75% automation test scripts using Selenium WebDriver and executed them

● Hands-on experience working on different testing techniques - Smoke testing, Sanity testing, Functional testing, Integration testing, Regression testing, Positive testing, Negative testing, Blackbox testing, UAT testing, Unit testing, Cross Platform testing, Database testing

● Post joining the team, the number of defects identified and reported improved by 80% in 6 months’ time compared to the defects raised earlier

● Increased the performance of the app by defect identification and management through JIRA and Confluence

● Performed regression testing at regular time intervals to maintain the stability of the app

● Contributed to 90% of the defects identified and were accepted by the development team as valid defects

● Constantly involved in providing feedback and suggestions to the development team in terms of UI and UX of the app

● Allocated to multiple projects simultaneously with 100% allocation expectations on both projects. Was able to match and improve the goals set by the teams

● Key member in the decision-making process, resource allocations and interaction with the client

● Involved in Software Development and Testing Life Cycle using Agile methodologies (scrum) and waterfall model PROJECTS

ANALYSIS OF CLIMATE CHANGE ON HUMAN BEHAVIOR AND VICE VERSA Mar 2017-May 2017

● Implemented techniques like SVR, Heat-Map Visualizations, Linear regression, correlation of features, decision tree regressor, random forest regressor for analysis of climate change on human behavior

● Implemented sentiment analysis for analysis of human behavior on climate change DOCUMENT CLUSTERING USING LDA, LSA AND WORD2VEC Jan 2017-May 2017

● Implemented dimensionality reduction techniques such as LSA, LDA and Word2Vec for word clustering on Amazon Reviews for Clothing, Shoes and Jewelry dataset and Enron Email dataset

● Implemented k-means clustering, Hierarchical clustering and Density Based clustering on both the datasets PREDICT THE OVERALL RANKING OF A FOOTBALL PLAYER Aug 2016-Dec 2016

● Collected, preprocessed and visualized the data required for our analysis

● Implemented machine learning techniques like test-train split, cross-validation technique, mean squared error, absolute error, Linear Regression, Lasso Regression, Ridge Regression and Random Forest SENTIMENT ANALYSIS OF TWEETS OF DIFFERENT TELEVISION SERIES Aug 2016-Dec 2016

● Collected the tweets from Twitter and preprocessed it for analysis

● Implemented K means clusters and performed sentiment analysis on the tweets

● Statistically displayed the data after analysis from the pickle file ACHIEVEMENTS

● Nominated and received the employee of the month award for two consecutive months in 2015

● Received appreciation emails from client and product owners for the work accomplished

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