Gayathri Sanjeev
About Gayathri Sanjeev
Gayathri Sanjeev is a Senior Data Analyst at Index Exchange in Toronto, Ontario, Canada, where she has worked since 2021. She specializes in data automation and integration, leveraging her extensive background in data science and programming.
Work at Index Exchange
Currently, Gayathri Sanjeev serves as a Senior Data Analyst at Index Exchange, a position she has held since 2021. In this role, she has implemented significant improvements in reporting processes. She set up an internal database from an existing supply chain database, which enabled faster report generation and manipulation using Oracle SQL. Additionally, she automated daily, monthly, and yearly supply chain reports using Python, significantly reducing production time from over two days to just two hours.
Education and Expertise
Gayathri Sanjeev holds a Bachelor of Technology (B.Tech.) in Information Technology from Amrita Vishwa Vidyapeetham, Bangalore, where she studied from 2005 to 2009. She furthered her education by obtaining a Master of Science in Applied Data Science from Syracuse University between 2018 and 2020. Additionally, she studied Big Data and Social Analytics at the Massachusetts Institute of Technology for 11 months in 2016. Her educational background provides her with a strong foundation in data analysis and technology.
Background
Before joining Index Exchange, Gayathri Sanjeev accumulated extensive experience in data analysis and programming. She worked as a Senior Data Analyst at Rogers Communications from 2020 to 2021 and as a Change Analyst at Vodafone Global Enterprise from 2013 to 2017. Her early career included a role as a Senior System Engineer at Vodafone Business in Bangalore, India, from 2009 to 2013. She also gained experience as a Data Scientist Intern at CONNECT asset management in 2019.
Achievements in Data Analysis
Throughout her career, Gayathri Sanjeev has developed tools and processes that enhance data analysis capabilities. She integrated SQL into Python for data cleaning and feature addition, which improved exploratory data analysis. Notably, she created a Stock Balancing Tool using Python and SQL, which improved productivity time from 5-6 hours to less than an hour. Additionally, she produced a product launch tool that provided insights on product launch status through map visualizations and graphs.