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Applied Scientist, Pricing and Promotion Optimization

Job in Seattle, King County, Washington, 98127, USA
Listing for: Amazon
Full Time position
Listed on 2026-02-20
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Analyst, Data Scientist, AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Applied Scientist, Pricing and Promotion Optimization

Job  |  Services LLC

Amazon's Pricing & Promotions Science is seeking a driven Applied Scientist to harness planet‑scale multi‑modal datasets, navigate a continuously evolving competitor landscape, and regularly generate fresh customer‑relevant prices on billions of Amazon and Third Party Seller products worldwide.

We are looking for a talented, organized, and customer‑focused applied researcher to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer‑obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.

This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross‑functional collaboration skills, business acumen, and an entrepreneurial spirit. You should be a self‑starter, comfortable with ambiguity, demonstrate strong attention to detail, and thrive in a fast‑paced, ever‑changing environment.

Key Job Responsibilities
  • See the big picture:
    Understand and influence the long‐term vision for Amazon's science‑based competitive, perception‑preserving pricing techniques.
  • Build strong collaborations:
    Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale.
  • Stay informed:
    Establish mechanisms to stay up to date on the latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi‑objective optimization techniques, and identify opportunities to apply them to relevant Pricing & Promotions business problems.
  • Keep innovating for our customers:
    Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.
  • Successfully execute & deliver:
    Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.
A Day in the Life
  • Invent and deliver price optimization, simulation, and competitiveness tools for Sellers.
  • Shape and extend our RL optimization platform – a pricing‑centric tool that automates the optimization of various system parameters and price inputs.
  • Promotion optimization initiatives exploring CX, discount amount, and cross‑product optimization opportunities.
  • Identify opportunities to optimally price across systems and contexts (marketplaces, request types, event periods).

Price is a highly relevant input into many partner‑team architectures and to the customer; this role creates the opportunity to drive extremely large impact while demanding careful thought and clear communication.

About the Team

The Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet‑scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization.

We preserve long‑term customer trust by ensuring Amazon's prices are always competitive and error‑free.

Basic Qualifications
  • PhD or Master's degree and 4+ years of experience in Computer Science, Electrical Engineering, Machine Learning or related field.
  • Experience programming in Java, C++, Python or a related language.
Preferred Qualifications
  • Experience building machine learning models or developing algorithms for business application.
  • Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
  • Experience with training and deploying machine learning systems to solve large‑scale optimizations.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or…

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