We are seeking a scientist with rigorous training in A/B testing and observational causal modeling (e.g. synthetic controls, causal matrix completion). Our team owns "causal inference as a service" for the Pricing and Promotions organization; we run A/B tests on new pricing, promotions, and pricing/promotions CX algorithms and, where experimentation is impractical, conduct observational causal studies.

Key job responsibilities
We are seeking a scientist excited to build the next generation of pricing, promotions, and pricing/promotions CX for Amazon. On our team, you will work at the intersection of economic theory, statistical inference, and machine learning to design and implement in production new statistical methods for measuring causal effects of an extensive array of business policies.

This position is perfect for someone who has a deep and broad analytic background, is passionate about using mathematical modeling and statistical analysis to make a real difference. You should be familiar with modern tools for data science and business analysis and have an interest in working with engineers to put projects into production. We are particularly interested in candidates with research background in experimental statistics.

A day in the life
A day in the life

Discuss with business problems with business partners, product managers, and tech leaders
Brainstorm with other scientists to design the right model for the problem at hand
Present the results and new ideas for existing or forward looking problems to leadership
Dive deep into the data
Build working prototypes of models
Work with engineers to implement prototypes in production
Analyze the results and review with partners

About the team
We are a team of scientists who design and implement the econometrics powering pricing, promotions, and pricing/promotions CX.