×
Register Here to Apply for Jobs or Post Jobs. X

Applied Scientist, Pricing and Promotion Optimization

Job in Seattle, King County, Washington, 98127, USA
Listing for: Amazon
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Analyst, Machine Learning/ ML Engineer, 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

Description

Amazon's Pricing & Promotions 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 and Third Party Seller products worldwide.

We are looking for a talented, organized, and customer-focused applied researchers 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. 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 in a fast-paced and 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 latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. 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

We are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through:

  • 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.

  • Identifying 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 is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.

About the team

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 CS, CE, ML or related field experience

  • Experience programming in Java, C++, Python or 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 adjustment during the application and hiring process, including support for the interview or onboarding process, please visit (Use the "Apply for this Job" box below). for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision,…

To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)

Job Posting Language
Employment Category
Education (minimum level)
Filters
Education Level
Experience Level (years)
Posted in last:
Salary