Software Engineer

Sandeep Subhash Madnaik

**************@*****.*** +1-669-***-**** San Jose, CA LinkedIn: sandeep-madnaik Github: sandeep-madnaik SKILLS:

Languages: Java, J2EE, Python, C, C++, JavaScript, Ruby; HTML5, CSS3, AngularJS, ExpressJS, NodeJS, XML, JSON Frameworks: Collections, Hibernate, Spring MVC, Spring Batch, JDBC, Servlets, JSP; Log4J, JUnit, REST, Hadoop, MapR, Docker Servers & Databases: Apache Tomcat, Jetty, Flask, JBoss; Oracle 9i/10g, MySQL, PostgreSQL, MongoDB Tools & Cloud Technologies: Git, Mercurial, Jenkins, Maven, Jira; GCP, AppEngine, Amazon Web Service (AWS), Kubernetes EDUCATION:

Master’s in Computer Science, San Jose State University, San Jose, CA May '20 Select Coursework: Big Data Analytics & Machine Learning (Map-Reduce, ELK Stack, Apache Drill, Kafka, & Spark), Cryptography

& Computer Security, Web Intelligence (Mining of massive datasets), Data Science, Topics in Database System, Distributed Systems, Data Structures, Operating Systems, Computer Networks, Advanced Computer Architecture. Bachelor’s in Computer Science and Engineering, Solapur University, MH, India Sep. '10 - Jun. '13 RELEVANT WORK EXPERIENCE: [3 years, 9 months]

Java Software Engineer, for Innovative Intelligent Solutions, Inc., Fremont, CA, USA [6 months] Feb. ’20 – Jul ‘20

• Involved in the development of Presentation layer using JSP, HTML5, CSS3 and used Spring MVC framework

• Worked in implementation of MVC design paradigm of Spring MVC framework, object-relational mapping (ORM) using Hibernate and Oracle database at the back end

• Used Continuous Delivery / Continuous Integration (CD/CI) tools, Docker, Jenkins to deploy the application to AWS Software Engineer, Intern for Tuutkia, LLC, Fremont, CA, USA [9 months] Apr. ‘19 - Jan. ‘20 Developed a web application for inventory management system and tested REST APIs with PostMan [Java, Spring MVC, REST]

• Created DAO layer for system as well as helped improve MySQL database schema

• Ensured bug fixes for all project modules and unit tested by writing test cases in JUnit Senior Systems Engineer for Infosys Limited, Pune, India [2.5 years] Oct. '13 - Apr. '16 Dispute Resolution System [21 months]: A web application aimed to resolve discrepancies occurring during credit card transactions for a payment technology solutions company [Jira, Spring MVC, Spring Boot, JUnit, Hibernate, REST, AngularJS]

• Contributed as a part of a team of 25 in an Agile SDLC from analyzing customer requirements, documenting a HLDD, coding, and unit testing modules in every sprint and handled Change Requests after each sprint

• Led a team of 4 to execute code clean-ups and various regression check activities to boost application's performance by more than 20%

• Created REST calls for whole project & maintained code logs for each action to be taken from mainframe

• Presented modules to client after each Agile sprint and accommodated changes suggested by client AccessPLUS Metadata [5 months]: A metadata related project to provide support to credit-card company products with respect to communication with mainframes using COBOL [Maven, JSON, XML, MySQL, Spring Batch]

• Developed in a small team of 3 for a horizontal project to provide Metadata support for 3 vertical projects

• Maintained synchronization of Metadata between credit card mainframe systems and web application PROJECTS:

Note tracking application with MEAN stack [MongoDB, ExpressJS, AngularJS, NodeJS, Angular Material] Jul. ‘20

• Built a note application with CRUD functionality with Angular Material to create a pristine User Interface (UI)

• Improved application functionality with advanced features such as sorting with dates and groups Predicting Students’ Performance using Learning Analytics [Scikit-learn, Jupyter Notebook, MatPlotLib] May. '18 – Apr. '19

• Predicted student grades with different models based on various features extracted from a student dataset

• Identified major social factors affecting students’ performance and suggested drop-out rates for students Image Classification using Deep Neural Networks [Python, Keras, TensorFlow, Flask] Apr. '18 – May '18

• Applied a Deep Neural Network on a Kaggle dataset to classify images into cats & dogs with 96% accuracy

• Applied a 5-layer network with Keras & a Flask web application to demonstrate resulting predictions Adaptive Self-Help Programming Exercises with LMS Integration [Scala, Java, GCP, PostGreSQL] Aug. '17 - Dec. '17

• Implemented an adaptive system for providing practice coding challenges for university students, suited to comfort levels, with Scala in Play framework

• Coded dynamic problem generation capability to existing LTIHub and deployed it on Google Cloud Platform Comparison of K-means Clustering Using WEKA & Mahout [Python, Weka, Mahout, AWS] Oct. ‘17 - Dec. '17

• Clustered a feature-rich large video game dataset with WEKA to identify similar games

• Deployed Mahout code on AWS and Elastic Map Reduce to cluster similar games together from dataset Sentiment Analysis on Movie Database [Python, Spark, Jupyter Notebook, NumPy, Pandas] Oct. '16 - Nov. '16

• Classified sentiments from a huge movie review database into positive and negative with Apache Spark and techniques such as TF-IDF, Word2Vec in a Linux environment Data Analytics on Enron Dataset [Python, scikit-learn, Sublime Text Editor, MapR] Sep. '16

• Performed data analysis from Enron dataset to identify Person of Interest from hundreds involved in company fraud

• Applied SVM and Random Forest as learning models to analyze data and compare results

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