STAFF, DATA SCIENTIST

Merchandising Data Science builds the systems — both automated decision engines and decision support systems — that drive high-stakes merchandising decisions: how we select and curate items, manage space, plan and allocate inventory, flow inventory through the network, decide what and how much to buy, read the competitive landscape, and price. As a Staff Data Scientist, you own a single, hard problem end-to-end — not an abstract domain, but a specific question like "how do we estimate price elasticities better?", "how do we reduce forecast error for seasonal items a year out?", or "how do we incorporate all constraints at DC outbound so the planned flow can actually be executed, exceptions and all?" Depending on the problem, the answer is a system that decides automatically, or one that gives a merchant or planner the right recommendation, tradeoff, and evidence to decide well.