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Software Engineer Data

Location:
San Jose, CA
Posted:
March 20, 2020

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Resume:

Siddarth Varanasi

+1-669-***-**** www.linkedin.com/in/siddarthvaranasi https://github.com/sid1694 adcdjx@r.postjobfree.com San Jose, CA-95112

EDUCATION

Master’s in San Jose State University Jan’ 2019-Present Key Courses: Enterprise Software Platforms, Software Systems Engineering, Cloud Technologies, Enterprise Distributed Systems, Data Mining, Large Scale Analytics

Bachelor's in Osmania University Aug’ 2011-May 2015 Key Courses: Data Structures, Algorithm Analysis and Design, Database Design, Operating Systems EXPERIENCE

Sr. Software Engineer, Cognizant Technology Solutions Feb’ 2017 – Dec’ 2018

● Participated in all stages of Software Development Life Cycle in a highly dynamic, fast paced environment.

● Designed a light-weight application for ingesting customer data and performing analytics using Design Patterns, Service Oriented Architecture, Java, MongoDB, Kafka.

● Was part of design reviews with Business to identify KPIs and understand the use cases needed to define the functionality of the system. Prepared the Requirements Documents for reference.

● Wrote high quality, modular, scalable code using Java, Spring, Oracle, ActiveMQ, JUnit, Mockito.

● Participated in code reviews. Performed Unit Testing, Functional Testing, User Acceptance Testing.

● Mentored and trained junior software engineers, engaging in pair programming. Software Engineer, Cognizant Technology Solutions Jan’ 2016 – Feb’ 2017

● Used Java, J2EE, RESTful web services, Maven, Apache to design and develop payments’ applications for a leading health care provider.

● Worked with cross functional teams to understand business requirements, in an Agile environment.

● Developed the UI of the applications & dashboards using HTML5, CSS, Bootstrap and JavaScript.

● Wrote automated tests using Selenium to reduce the time for testing the application by 50%.

● Developed REST APIs by extracting structured and unstructured data from various sources to provide business solutions to identify anomalies and phishing attacks to the billing platform.

● Was involved in production support, involving customer reviews providing hot bug fixes using Kibana dashboards. TECHNICAL SKILLS

● Programming Languages: Java, C, C++

● Web Technologies: HTML5, CSS 3, PHP, JavaScript, Node.js, Express.js, React.js, REST, GraphQL.

● Databases: SQL, MySQL, Mongo DB.

● Operating systems: Windows, IOS, LINUX/UNIX

● AWS Cloud Technologies: AWS RDS, Elastic Compute, Elastic load balancer, Elastic block Storage.

● Miscellaneous: Object Oriented Programming, Data Structure, Algorithms, Design Patterns, Service Oriented Architecture, REST, SOAP, Apache, JUnit, LINUX/ UNIX, Bash, Shell Scripting, Selenium, websphere / web-logic, WebDriver, TestNG, JSystem, JUnit

ACADEMIC PROJECTS

● Training Management System: Built a portal to enable, manage, schedule and assess training programs for students using Core Java, MySQL, HTML and CSS, Multithreading.

● GitHub Simulator: Developed a console application: created as a code sharing platform on the lines of GitHub to push code, create a fork of repositories, follow/unfollow users, create pull requests using Core Java, MySQL, Shell Scripting. Deployed the application to EC2 instance.

● Marketplace: An e-commerce website created to buy and sell a range of products online. Developed a recommendation system to provide results to the customers based on previous searches, by implementing content-based filtering. Deployed the application into a Docker instance. Used PHP, MySQL.

● Social Recommender System: Built the system by extracting interests from user activities using clustering algorithms (K- means, DBSCAN) . Evaluated the clusters using analysis algorithms and recommended social interests for each user in twitter using Twitter API for data and analysis.

● Genre Prediction based on movie plots: Built a prediction system using multi label classification, data scraping, data cleaning, text processing and modelling. Compared efficiency of the two algorithms namely MultinomialNB and LinearSVC using Pandas, NumPy & SciPy libraries in Python.



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