Applied Scientist, Ads Econ

Amazon
Culver City, CA, USA / New York, NY, USA / Seattle, WA, USA2026-04-21ONSITE

About the job

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Our products are used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. We are looking for an experienced Applied Scientists who have a deep passion for building machine-learning solutions, ability to communicate data insights and scientific vision, and execute strategic projects.

Responsibilities

Build full life-cycle machine learning solutions; build models and perform data analysis to deliver scalable solutions to business problems.

Scale ad performance insights through agentic systems/LLMs.

Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.

Work closely with software engineers on detailed requirements to productionize the ML models you build.

Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.

Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.

Research innovative machine learning approaches.

Qualifications

Minimum

PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field

3+ years of experience of building machine learning models for business application

Experience programming in Python or related language

Preferred

Experience using Unix/Linux

Experience in professional software development

PhD