Applied Scientist, Price Perception and Evaluation Science

Amazon • Seattle, WA

5h

About The Position

Amazon's Price Perception and Evaluation team is seeking a driven Applied
Scientist to harness planet scale multi-modal datasets, and navigate a
continuously evolving competitor landscape, in order to build and scale an
advanced self-learning scientific price estimation and product understanding
system, regularly generating fresh customer-relevant prices on billions of
Amazon and Third Party Seller products worldwide.

The Applied Scientist will work closely with other research scientists, machine
learning experts, and economists to design and run experiments, research new
algorithms, and find new ways to improve Seller Pricing to optimize the Customer
experience. The Scientist will partner with technology and product leaders to
solve business and technology problems using scientific approaches to build new
services that surprise and delight our customers.

Requirements

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language

Nice To Haves

• Experience building machine learning models or developing algorithms for business application
• Experience applying theoretical models in an applied environment
• Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices
• Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences

Responsibilities

• Research and use of statistical techniques to create scalable solutions for business problems.
• Design, build, and deploy effective and innovative ML solutions to provide low prices and increased selection for customers using scientifically-based methods and decision making.
• Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation.
• Publish and present your work at internal and external scientific venues.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree