Gaurav Panthari Email & Phone Number

Seoul, Seoul, Kr

Seattle, Wa, Us

Amazon Fulfillment Technology (AFT)

Seattle, Wa, Us

Amazon Fulfillment Technology (AFT) powers physical Fulfillment Centers (FCs) for goods our customers buy on Amazon world-wide and is powered by software systems that are designed to handle billions of transactions between the physical processes and the Amazon Supply Chain. Within AFT, I work with teams responsible for building solutions to optimize FC shift planning, staffing and flow management. These systems integrate with labor management softwares using complex algorithms to automate staffing decisions taking efficiency in account while also prioritizing associates' health and safety.

Seattle, Wa, Us

Amazon Associates Program operates in all countries that Amazon operates in, with a mission to engage customers whenever they are off Amazon and influence their product discovery and shopping decisions through affiliates. The program compensates publishers for traffic they drive to Amazon.Within the Amazon Associates Program, I was part of a team working on creating automated and manual systems to detect malicious activities of an affiliate in the program, with a focus on large scale data mining, machine learning and analytics. The team worked on developing and enhancing tools that help in detecting potential suspicious actors and identifying outliers, who would be using fraudulent activities that were not allowed/were unethical as part of Amazon Associates Program.

New York, Ny, Us

Worked as a Consultant for Morgan Stanley at client location for SPG group. I worked on development of tools and interfaces used by traders in Morgan Stanley while booking/managing a trade with their clients. The tools provide various details related to a bond, which help the traders in dealing with clients. My work also included working on the enhancements requested by the traders, along with constantly researching on reducing the response time of the applications.

Hyderabad, India , Us

Worked on client side assignment for Morgan Stanley

Suwon-Si, Gyeonggi-Do, Kr

- Handled the regional adaptation (Customer Specific Customization) of Samsung Smart Phones/Tablets that are launched in different parts of the Globe with operator/region specific data to be applied as per requirement from the operator/of the region.- Worked in Accessibility module in Settings.

Mumbai, Maharashtra, In

Client: Maersk A/S EuropeProject Title: Single Customer ViewDescription: A web based platform where all basic customer information can be housed. It is the foundation project of a future Customer Relationship Management solution. The main Business/ Operating process areas of Single Customer View:Access to customer information across touch points Search for and view specific customer information Update customer information in a structured format Maintain the customer information quality by introducing a control and validation process for all updates. Responsibilities heldCode development.Checking performance of the written code using Jprofiler.Handing Defect Prevention activities in Project. Defects were tracked, reviewed, analyzed and compared using Track tool.Respond to user issues, investigated and troubleshoot the bugs in test and production environment.Analysis, Design and Construction of various CRs and PRs.Test planning, test case estimation, test schedule and writing high level scenarios and & test cases for integration and system testing.High Level Scenario Writing, Business/System/Regression Test Case WritingCreating \ Executing Test Scenarios for various phases of testing : - Unit Testing- System Testing- Integration testing- Unit Acceptance Testing- Performance testing

Le Chesnay Cedex, France, Fr

Subject: Extracting Sequential Patterns at Optimum Time GranularitiesWorked on finding new techniques in the field of data mining to obtain the frequent sequential patterns among a very large set of transaction sequences in whole database or in some part of the database. Later the work included expanding the concept of Prefixspan algorithm to make it work for finding frequent patterns either in whole of the database or in some part of the database along with their period of frequency.