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Principal Applied Scientist, Simulation and Experimentation Team
Principal Applied Scientist, Simulation and Experimentation Team-March 2024
Seattle
Mar 28, 2026
About Principal Applied Scientist, Simulation and Experimentation Team

  Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of devices (Kindles, Fire tablets, Fire TV, Alexa, mobile, Twitch, and more). We start with the customer and work backwards in everything we do, including advertising. If you're interested in joining a rapidly growing team working to build a unique, highly respected advertising group with a relentless focus on the customer, you've come to the right place.What does Publisher Services, the hiring team, do?The Publisher Services team within Amazon Advertising is building the next generation of products and services that will fuel the growth of Amazon's advertising business. We own the customer facing facets of Amazon's Supply Side Technologies, which allow publishers to monetize their on-demand, streaming, and static placements across Amazon's ad network in a few clicks. Publishers interact directly with our technology, through our website and/or programmatic APIs and get enterprise-grade access to optimize billions of impression opportunities per day.What is the Publisher Services team looking for?We are looking to build out our Simulation and Experimentation team to drive innovation across our product. As a principal scientist, you will apply cutting edge designs and methodologies for complex use cases across Publisher Technologies to drive innovation. In addition, you will contribute to the end state vision for simulation and experimentation of Publisher Technologies at Amazon.This is a rare opportunity to kick-start a completely new user experience at Amazon. You will be a foundational member of the team that builds a world-class, green-field simulation and experimentation for the Amazon Supply-Side Technologies in Advertising.Key job responsibilities* Developing new statistical, causal, machine learning, and simulation techniques and develop solution prototypes to drive innovation* Working with technical and non-technical customers to design experiments, simulations, and communicate results* Collaborating with our dedicated software team to create production implementations for large-scale data analysis* Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business* Presenting research results to our internal research community* Leading training and informational sessions on our science and capabilities* Your contributions will be seen and recognized broadly within Amazon, contributing to the Amazon research corpus and patent portfolio.We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USA- PhD in statistics, mathematics, operations research, computer science, or a related field- 10+ years of applied research experience- Experience programming in Java, C++, Python or related language- Multiple years of experience working with large-scale, complex datasets to create/optimize statistical, machine learning, simulation, forecasting, and/or optimization models.- Strong problem solving and analytical abilities- Experience with modeling tools such as R, scikit-learn, Spark MLlib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems- Experience with AB testing framework and experimental design- Experience with graphical causal models and causal ML methodologies- Experience with discrete event simulation and agent based models- Proven experience leading the delivery of large-scale, high-quality systems- Experience working on automated marketing technologies- Experience working on ad

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