Data Information

EDUCATION:

Stevens Institute of Technology, Hoboken, NJ

Master of Information Systems

Relevant Courses: Big Data Technologies, DA&ML, Data Warehousing, Data Management Narsee Monjee Institute of Management Studies, Mumbai, IN Bachelor’s in Information Technology

Relevant Courses: DBMS,

TECHNICAL

SKILLS:

WORK

Languages: Python, R, SQL, Ext JS

Tools: Apache Spark, Git, Tableau, Atlassian tools (JIRA, Confluence) Accenture Solutions Pvt. Ltd, Mumbai, IN

EXPERIENCE: Application Development Analyst Nov 2016 - Jun 2019

• Developed various UI screens, multiple modules as part of sub story and Agile Methodology in Ext JS.

• Fixed multiple client requested sub-stories (about 6) and defects (about 110+, Minors - 65, Majors - 35+, Critical - 10).

• Discussed and negotiated scope of Change Requests and implemented them to be included in the production.

• Lead a module responsible for unit test backlog and increased code coverage from 20% to 85% with karma, SonarQube in Ext JS.

• Designed test cases and tested webservices using SOAP UI to measure the functionality coverage of each module.

• Closely worked with client and documented the requirements using Atlassian tools to meet end product design.

• Proposed multiple solutions to queries related to look and feel of different pages to the client.

• Documented the dataflow and workflow of the application from front end to backend using Confluence. IGATE Global Solutions Ltd, Mumbai, IN

Software Testing Intern May 2016 – Jun 2016

• Tested functionality of a dashboard application that helped identifying and reporting multiple gaps, defects and discrepancies between application and design requirements.

• Reported and logged over 200 bugs on JIRA and defects which ensured that product is compliant with functional specifications as a part of Integration and Accessibility testing. ACADEMIC Pharmaceutical Data mining April 2016

WORK: Developed a system to identify and predict similar drugs based on their molecular information while training the system using Support Vector Machines. The system has the capability to display each molecule fed to it as a graph of atoms. Achieved an accuracy of 61% using just the bond information of the molecules. Data Scaling Study (Big Data Technologies) February 2020

• Classified stock market data using various algorithms like linear regression, decision tree and gradient boosted tree.

• Compare these models and noted the performance in the metrics - execution time and accuracy.

• Noted changes/effects on execution time and accuracy of all the algorithms with varying volumes of data. Performed comparative study on AWS-EMR (varying number of clusters) and local machine to observe execution time and accuracy in PySpark.

KHUSHBOO BABARIA

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