Applied Scientist, Price Perception & Evaluation Science

Amazon; Seattle (WA); On-site; USD 142,800 - 193,200; Full time

Benefits offered by this job

Health insurance

Sign-on payments and RSUs

Job summary

Amazon’s Price Perception and Evaluation team seeks an Applied Scientist to harness planet-scale multi-modal datasets to build an advanced self-learning price estimation and product understanding system, generating fresh, customer-relevant prices across billions of products worldwide.

Responsibilities include designing ML solutions, evaluating them with offline tests and online A/B tests, and publishing findings at internal and external venues, contributing to scalable data analyses and

Qualifications

• 3+ years of building models for business applications.
• PhD or MS with 4+ years in CS/CE/ML or related field.
• Experience with patents or publications in top-tier venues.
• Proficiency in Java, C++, Python or related language.
• Experience building ML models for business applications.
• Experience applying theoretical models in an applied environment.
• Experience using generative AI tools to improve workflow.
• Ability to identify opportunities for AI to enhance products.

Responsibilities

• Research and apply statistical techniques to solve business problems.
• Design, build, and deploy ML solutions to provide low prices and increased selection for customers using scientifically-based methods.
• Evaluate proposed solutions via offline benchmarks and online A/B tests in production.
• Establish scalable, automated processes for large-scale data analyses, model development, validation and implementation.
• Publish and present work at internal and external scientific venues.

Skills

Java

C++

Python

ML modeling

Generative AI

AB testing

Education

PhD

MS in CS/CE/ML

Job description

Amazon’s Price Perception and Evaluation team seeks an Applied Scientist to harness planet-scale multi-modal datasets to build an advanced self-learning price estimation and product understanding system, generating fresh, customer-relevant prices across billions of products worldwide.

Responsibilities include designing ML solutions, evaluating them with offline tests and online A/B tests, and publishing findings at internal and external venues, contributing to scalable data analyses and