mid machine learning Applied Scientist ic Bachelor's · Posted Mar 2, 2026
$142,800 – $193,200
USD per year

About this role

Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Seattle, WA. The posting calls out experience with Python, Java, Reinforcement Learning, Distributed Systems. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $142,800–$193,200 per year.

Role
Applied Scientist
Function
machine learning
Level
mid
Track
Individual contributor
Employment
Full-time
Location
Seattle, WA
Education
Bachelor's degree
Department
Applied Science
Posted
Mar 2, 2026
AI Summary
Applied Scientist developing machine learning models for Amazon's pricing optimization across billions of products. Requires expertise in ML, causal inference, reinforcement learning, and experimental design. Collaborate cross-functionally to deploy pricing algorithms at scale and drive business impact.

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Job description

from Amazon careers

Amazon's Pricing Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon products worldwide. We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our pricing algorithms across all products listed on Amazon. This role requires an individual with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, excellent cross-functional collaboration skills and business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work independently to deliver business impact. Key job responsibilities - See the big picture. Understand and develop science to influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques - Build strong collaborations. Partner with product, engineering, and data teams within Pricing Promotions to deploy models at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, reinforcement learning, causal ML, and…

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