Are you passionate about solving complex problems that impact millions of customers? Join Amazon's Supply Chain Optimization Technologies (SCOT) Long-Term Planning team, where you will architect the future of the world's most advanced fulfillment network.
As an Applied Scientist on our team, you will drive multi-billion dollar investment decisions that shape Amazon's global fulfillment strategy. You will pioneer innovative solutions using operations research, machine learning and statistical techniques, directly influencing Amazon's ability to delight customers while optimizing billions in capital investments. Your insights and recommendations will be presented to the highest levels of senior leadership, helping guide company-wide strategy.
In this role, you will develop our next-generation Multi-Tier Marginal Benefit Analysis (MT-MBA) platform. This involves creating sophisticated forecasting models that power network expansion decisions, transforming complex supply chain challenges into elegant mathematical solutions. You will design and implement novel algorithms that optimize warehouse placement, timing, and capacity, all while leveraging advanced machine learning techniques and large-scale optimization modeling.
You will join our Long-Term Planning Organization within SCOT, working alongside world-class applied scientists, economists, research scientists, product managers, and software engineers. We are seeking innovative thinkers who can balance theoretical excellence with practical implementation. Your ability to communicate complex technical concepts and drive data-driven decisions at massive scale will be crucial to your success.
