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.…
What we'd score you on
reqspace match rubricFive 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.
Score yourself on this role.
Free · no card · written explanation included
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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