Padmapriya Thulasiram

Work History

Amazon

4 2020 - Current

Analyzed the data and highlighted the gaps, recommending solutions, driving inter- function and decisions
Identified possible improvements in the processes and suggested ways of implementation for the needed changes
Managed daily volumes of assigned work and ensured compliance with quality standard
Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders for concise explanations of the best placement for needed resources.
Identified process gaps through value stream mapping exercises, implemented process enhancements and automation to increase throughput
Increased the buy-ability/yield of products on the website by analyzing customer views, percentage of insufficient data and broken detail pages
Created and shared relevant executive reports while keeping them updated on the progress of various projects.
Leveraged text, charts and graphs to communicate findings in an understandable format.
Analyzed large amounts of data to identify trends and find patterns, signals and hidden stories within data.
Used business objects, business intelligence and other reporting tools to extract data from data solutions and data warehouses.
Managed a program across multiple geographical locations

Amazon

08.2016 - 04.2020

Populating and proposing content for the Product catalog on the Amazon websites
Participated in the identification and correction of catalog errors, investigating catalogue-related complaints
Identified possible improvements in the processes and suggested ways of implementation for the needed changes
Worked with senior TPMs, Developers in building global tools for internal teams in Amazon.
Managed Q.B.R.'s (Quarterly Business Reports), MBR's (Monthly Business Reports), S.L.A metrics, and KPIs.
Led root cause analysis initiatives to identify and rectify errors, resulting in improved team productivity and enhanced quality standards.
Collaborated closely with technology teams to facilitate the development of machine learning models aimed at automating manual processes