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AmazonApplied Science

Pricing Applied Scientist, Pricing Science

USonsitemid$143K – $193K

Posted 4 days ago · via Amazon

About this role

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 pricing decisions at scale: demand lift models, customer lifetime value frameworks, and the experimentation infrastructure that validates whether our pricing changes actually work. We're hiring an Applied Scientist to own causal inference at the intersection of ML and pricing experimentation. This role exists because our team has identified a real gap: the methodological bridge between econometric analysis (owned by our economists) and production-scale ML pipelines (owned by our engineers) needs a practitioner who lives in both worlds.…

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What we'd score you on

reqspace match rubric

Five dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.

1

Skills match

For this role: python, java, c++

2

Level fit

This role is mid-level. We check your trajectory against it.

3

Domain experience

Your work in the role's domain matters more than your years total. We weight recent and direct experience.

4

Recency

A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.

5

Location fit

This role is based in US. We weight your proximity and willingness to relocate.

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Skills in this role

Pulled from the job description. These are the keywords we'll weight when scoring your fit.

pythonjavac++

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