Applied Scientist, Publisher Ad Server Science + Simulation and Experimentation

Amazon Advertising's Publisher Technologies team is looking for an experienced Applied Scientist with proven research experience in control theory, online machine learning, and/or mechanism design to drive innovative algorithms for ad-delivery at scale. Your work will directly shape pacing, yield optimization, and ad-selection for Amazon's publishers and impact experiences for hundreds of millions of users and devices.

About the team
Amazon Advertising operates at the intersection of eCommerce, streaming, 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 customers across Amazon's owned and operated sites (publishers) across the web and on millions of devices such as Amazon.com, Prime Video, FreeVee, Kindles, Fire tablets, Fire TV, Alexa, Mobile, Twitch, and more. Within Ads, Publisher Technologies is building the next generation of ad-serving products to allow our publishers to monetize their on-demand, streaming, and static content across Amazon’s ad network in a few clicks. Publishers interact directly with our technology, through programmatic APIs to optimize billions of impression opportunities per day.

About the role
Publisher Technologies is looking to build out our Publisher Ad Server Science + Simulation and Experimentation team to drive innovation across ad-server delivery algorithms for budget pacing, ad-selection, and yield optimization. We seek to ensure the highest quality experiences for Amazon's customers by matching them with most relevant ads while ensuring optimal yield for publishers. As a Senior Applied Scientist, you will research, invent, and apply cutting edge designs and methodologies in control theory, online optimization, and machine learning to improve publisher yield and customer experience. You will work closely with our engineering and product team to design and implement algorithms in production. In addition, you will contribute to the end state vision of AI enhanced ad-delivery. You will be a foundational member of the team that builds a world-class, green-field ad-delivery service for Amazon's video, audio, and display advertising.

To be successful in this role, you must be customer obsessed, have a deep technical background in both online algorithms and distributed systems, comfort dealing with ambiguity, an eye for detail, and a passion to identify and solve for practical considerations that occur when complex control-loops have to operate autonomously and reliably to make millisecond level decisions at scale. You are a technical leader with track record of building control theoretic and/or machine learning models in production to drive business KPIs such as budget delivery. If you are interested working on challenging and practical problems that impact hundreds of millions of users and devices and span cutting edge areas of optimization and AI while having fun on a rapidly expanding team, come join us!


Key job responsibilities
* Developing new statistical, causal, machine learning, and simulation techniques and develop solution prototypes to drive innovation
* Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business
* 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
* Staying up-to-date with and contributing to the state-of-the-art research and methodologies in the area of advertising algorithms
* 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