Sign in

Engineer Software Developer

San Jose, California, United States
November 19, 2018

Contact this candidate



San Jose, California



Master of Science in Computer Engineering- GPA: 3.61 Dec 2018 San Jose State University, CA

Specialisation: Data Science; Data Mining, Machine Learning, Large Scale Analytics Bachelor of Engineering in Computer Science - GPA: 3.66 May 2015 SJB Institute of Technology(V.T.U), Bangalore, India Experience

Project Engineer, Wipro Technologies Aug 2015 - June 2017

● Developed a Full Stack Web application, an online vehicle booking system, in which I was mainly responsible for front end and database design and development.

● Worked with GlaxoSmithKline’s data migration and database decommissioning project.

● Responsible for analysis, extraction,verification, archival of data and databases and writing SQL queries.

● Consistent contribution helped the team secure full scale Customer Satisfaction rating from the clients. STEM Director & Software Developer - Intern, STEM4kids June 2018 - Aug 2018

● Proposed and developed a web application to assess students’ understanding through instant quizzes and report the performance to parents in which I was responsible for the application design and front end development. Skills

● Programming Languages:C, C++, Java, Python

● Web Technologies:HTML, CSS, Javascript, Bootstrap, Node.js, REST, MongoDB, MySQL

● Frameworks & Libraries:Express.js, jQuery, Spring MVC, Hibernate, JUnit, NumPy, Pandas, scikit-learn

● Tools: AWS Cloud9, Heroku, mLab, GitHub, Kanban, Eclipse Projects

● Machine Learning in a fully functional retail website Dec 2018 A fully functional e-commerce, Java-based Web application that uses machine learning principles to recommend products to buyers and features “Price Period Predictor”, a unique feature to predict price and duration of sale for users using the application as online sellers.

● YelpCamp Oct 2018

A Node.js responsive Web application developed on Cloud9 platform with mongoDB, EJS, Bootstrap and deployed on Heroku to share and improve one’s camping experience.

● Prediction of case status of H1B petitions May 2018 A machine learning model was developed to predict the case status of the filled H1B petitions leveraging various machine learning algorithms implemented in Python with prediction accuracy of 98 percent. Employers can take advantage of the model before filing employees’ petitions.

● Readmission predictor for diabetic patients May 2018 A machine learning model was developed to identify diabetic patients facing a high risk of future readmissions. The predictions showed an accuracy of 64.02 percent. Hospitals can use this model and prevent the readmissions by earlier, cheaper and milder treatments.

GitHub Link:


Web Developer Bootcamp online course, Udemy Nov 2018 Activities

Freelance Technical Trainer, Genesis Career Analytics July 2016

● Technical trainer for prospective professionals for campus recruitment.

● Courses: C, C++, Java programming languages; Data Structures in C; DBMS Microsoft Student Associate for #MSAIndia by Microsoft Corp. May 2018

Contact this candidate