Do you enjoy solving complex problems via the means of data analysis, math, statistics and automation? Do leveraging information retrieval, high performance computing and machine learning excite you? Are you thrilled by the thought of pushing technology to do things you never thought possible? In the world of E-Commerce business, have you ever wondered how B-to-C companies distribute millions of their products to different locations in order to maximize product availability to their customers while keeping the minimal inventory levels?
IPC Removal is responsible for managing Amazon’s inventory health by helping Amazon efficiently remove its unhealthy inventory stock and in turn optimizing the usage of limited Fulfillment Center’s resources and capacity. The challenge of IPC Removal system is to follow classic economic model to determine what’s healthy or unhealthy for different product categories and what rules can be best applied to determine the best next steps in the entire removal processes; to drive improvements in workflow for executing removals, adding improved visibility and data integrity. Reduce inventory stuck in the workflow and reduce removals defects; Contribute to the development of a global, real-time, event-driven PO tracking and assignment system. The IPC Removal system employs data mining technologies, statistics methodologies and computational algorithms to solve the sophisticated inventory controlling problems.