Amazon Applied Scientist II SCOT Long-Term Planning 

United States, Washington, Bellevue 

755990923

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.

- PhD, or Master's degree and 5+ years of building machine learning models or developing algorithms for business application experience
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- 3+ years of science, technology, engineering or related field experience
- Experience programming in Java, C++, Python or related language

- Experience in professional software development
- Demonstrated research experience in Causal Inference, Bayesian Modeling, or Optimization with a proven track record of publications at well-regarded conferences and journals