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Applied Scientist, Pricing Science

Pricing is one of the most consequential decisions Amazon makes — and the science behind it needs to be causally rigorous, not just predictive. The P2 Optimization Science (P2OS) team builds the machine learning systems that power Amazon's

In inglese

Company

Amazon

Location

Seattle, Washington, USA

Status

Open

Posted

2026-09-09T00:00:00+00:00

Amazon's P2 Optimization Science team is hiring an Applied Scientist to own causal inference for pricing. The work covers building, training, evaluating and deploying CATE estimation models, designing analysis workflows for pricing weblabs, and writing reusable causal ML tooling that economists and other scientists can use. The posting is explicit that this is not a research role: success is measured by changes in LTV estimates and pricing errors avoided, plus one internal methodology write-up per half. It asks for a PhD, or a master's plus four years' experience, and programming in Python, Java or C++.