Master of Science: Data Science

Post Graduate Diploma in Big Data Analytics

Bachelor of Engineering: Computer Engineering

Data Engineer Intern

• Engineered a mobile app to recommend laptops to users based on their input and certain parameters.
• Acquired data by utilizing python’s web scraping libraries such as BeautifulSoup and Selenium.
• Built meaningful reports to analyze factors affecting laptop prices and ratings using PowerBI.
• Created recommendation system to recommend laptops or cloud alternatives using python’s sklearn library.
• Performed sentiment analysis leveraging Pytorch using Natural Language Processing (NLP).
• Established a robust ETL pipeline using SQL which automated all the above tasks.

Trainee Software Engineer

• Controlled and optimized ETL pipelines utilizing SSIS, SSRS and SQL databases generating automated CCR
reports in retail sector for clients of US retail AI company.
• Oversaw ETL pipeline which retrieved required data from client database on YellowBricks containing Billions of
rows as per user’s time selection and generate automated reports for analysis.
• Managed and optimized 9 different types of reports each containing 5-16 different sub reports which accessed more
than 32 SQL datasets split into QA testing, staging and production which contains billions of rows.
• Migrated SQL databases, python scripts, SSIS and SSRS reports to Yellowbricks database.
• Optimized and created SQL Stored Procedures and ETL pipelines, resolved TFS bugs or Jira tickets from client
daily resulting in saving time generating reports.
• Developed more than 10 new reports and created automated pipelines as per monthly production release targets
posted on JIRA and managed more than 12 monthly production releases.
• Involved in 3 daily standup scrum calls (2 internal and 1 with client) following agile methodology.
• Designed SQL stored procedures such that the deliverables at the end of the month would be bug-free which saved
client’s time.
• Utilized Python, T-SQL, Microsoft SSMS, SSIS, and SSRS for programming stored procedures and report
generation. Performed analysis of reports as per client requirements and debugging of ETL pipeline to solve more
than 100 TFS bugs and Jira tickets.

Data Science Intern

• Created a python script using various classification machine learning algorithms such as logistic regression, svm,
decision trees, random forest, K-NN etc. to predict whether customer will make a deposit in the bank or not. Best
accuracy was 98% achieved by random forest.