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shalabh.neema@sjsu.edu

SHALABH NEEMA <BR>San Jose Bay Area XXXX@XXXX.XXX <BR>http://www.linkedin.com/in/shalabh-neema-11b43486 (XXX) XXX-XXXX Education <BR>Master in Software Engineering : San Jose State University Graduation- 2019 May 2021 <BR>Coursework: Enterprise Software Platform, Enterprise Distributed System, Software Engineering Process. <BR>Bachelors in Computer Science | IET DAVV, IN Graduation- 2012-Apr 2016 <BR>Coursework: Object Oriented Programming, Machine Learning, Analysis of Algorithms, Data Structures, Operating Systems, <BR>Computer Networks, Cloud Computing, Enterprise Resource Planning Skills: <BR> Programming Languages: Java, JavaScript, Python ,C++, C, HTML5, CSS, VB script, Android <BR> Frameworks & Technologies: React.js, Node.js, Kafka, Machine learning ,Redux, Redis, Flask, Selenium, Tesseract, Docker <BR> Tools & IDE: AWS ,HPQC, UFT, AutoIT ,Octave, Git, JIRA, IBM ClearQuest, Web Harvey, Eclipse, IntelliJ <BR> Databases: Oracle, MYSQL, MongoDB Work Experience: <BR>Software Engineer: Accenture | (2(XXX) XXX-XXXX) <BR>▪ Led a team of 4 in transforming 100+ automation scripts based on UFT to the Java & Selenium based framework which has <BR>reduced 40% cost of testing. <BR>▪ Built a Machine Learning model (Linear Regression) for estimating the cost of vehicle damage with an accuracy of 92%. <BR>▪ Developed the automation scripts using Java, Selenium and AutoIT to create more than 2500 end to end transactions per <BR>day which reduced the time of performance Testing by 65% and utilized Tesseract OCR for an image testing <BR>Associate Software Engineer: Accenture | (2(XXX) XXX-XXXX) <BR>▪ Developed 60+ comparison scripts in Java to validate the complex Dash Tool Reports with the data in Oracle Database in <BR>Keyword driven Testing framework using Adapter Design Pattern. <BR>▪ Automated the interactions between the isolated process like Defects logging in IBM ClearQuest, HPQC, Mimic policy <BR>submissions, result reports with automation scripts thereby improving the performance of the testing process by 95.87%. <BR>▪ Reviewed, monitored, and repaired any changed code for quality, adherence to standards, and potential performance effects <BR>of 120 regression scripts using Selenium and UFT by maintaining the code base of entire infrastructure. <BR>Projects: <BR>Mental Health Analysis in Tech Workers: <BR>▪ Developed a restful web application using React.js, Node.js & MongoDB which takes surveys from the users and provide <BR>prescriptive analysis to the users. <BR>▪ Built a Random Forest Classifier to predict whether a person in depression requires treatment with an accuracy of 91%. <BR>▪ Built a recommendation system based on Content based Filtering to assign a mentor to the person affected by depression. <BR>Starbucks Console Application Fall 2019 <BR>▪ Implemented Observer, Decorator, Chain of Responsibility and Strategy design patterns in Java. <BR>▪ Responsible for creating UML Class, Sequence and State diagrams to illustrate the design patterns used. <BR>▪ Integrated test cases to perform application level unit testing for different components. <BR>Prototype of Grubhub: <BR>Developed a restful web application which supports the Grubhub core use cases using Node.js, React.js, Redux, MySQL, <BR>MongoDB, Kafka and AWS . <BR>Weight Predictor : <BR>An Android application which helps in predicting the luggage weight for airport passengers <BR>▪ Built Linear Regression Model on the data extracted by the multi-threaded web scraper with an accuracy of 96%. <BR>▪ Lucid interface is designed that maps the Machine Learning model using Recycler View and Material Design. <BR>Achievements & Certifications: <BR>▪ Machine Learning by Stanford University by Andrew Ng with a score of 96.1% <BR>▪ Achieved 'Allstate Achiever’ and ‘Continuous Achiever’ award for outstanding performance in Allstate account.(Accenture).

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