- A highly committed, focused, and enthusiastic individual who strives for excellence in every undertaking.
- Technically sophisticated with strong proficiency in developing dynamic web-based projects, managing SDLC projects, and developing database applications
- Full-stack developer with 2+ years of experience in Web development.
- Skilled in Java, AngularJS, REST, HTML5, Object-Oriented Programming (OOP) concepts, Distributed Systems concepts, Data Visualization, Software Development Life Cycle, Core JAVA.
Technical Skills:
• Languages: Java, Python, Javascript, R, Spark, C, C++
• Client/Server Technologies: Angular, HTML 5, CSS 3, jQuery, AJAX, REST API, SOAP.
• Database/ Servers: Oracle, MySQL, Mongo DB
• Frameworks: Spring MVC, Spring Core, Hibernate, Apache POI, Jasper Reports, YOLO V3, Beautiful Soup, Selenium, Pandas, Skikit-learn, NLTK.
• Tools/Software: Eclipse, Spring Tool Suite, Postman, MongoDB Compass, SQL Developer, VSQL, Spyder, WinSCP, Putty, Power BI, Azure ML Studio, Git, SVN, GitHub, JIRA, Confluence, BitBucket, PowerApps, PowerBI, Microsoft Flow, Hadoop
-
Experience
● Designed and developed a web application with technology stack of React.js, Restful APIs where user
can access data and consolidated documentation.
● Framed a web app to capture and present logs generated by running core software.
● Built a frontend that consumed the API and presented a user-readable view of logs with searching, sorting, filtering.
● Facilitated file sharing and correspondence tracking with SharePoint.
-
Projects
Cloud Chat Server
Created a real-time chat-based application in which users can log in anywhere and chat with the available users.
Used AWS for deployment by creating EC2 instances for scaling.
Shopping Management System
● The system tracks the Recipes, Ingredients, and Shopping List of all the ingredients used with the database created in Firebase. ● Company-facing dashboard to add new products, authenticated with JWT role-based authorization.
● Used PayPal payment processor API to accept test credentials for payment validation.
Persistent Deletes in LSM-Trees (Research)
● Devised an efficient method for merging delete flags and their corresponding key-value pair, so the latency between a delete query and a true delete is shorter.
● Steps involve storing a separate delete data structure on disk with delete flags, maintaining timestamps, and merging based on a tuning knob, improving the latency of queries by 35%.
Predicting Bad Loans
● Carried out mini research on different methods of data classification/labeling problem. Implemented methods namely Decision Trees, Naïve Bayes, Logistic Regression, and Support Vector Machines.
● Used loan data from Lending Club USA and predicted whether the loan would default or not.