Principal Applied Scientist, Publisher Ad Server Science - Amazon

Description 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 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. You will research, invent, and apply cutting edge designs and methodologies in control theory, ranking, ad selection, 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 ad server 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 online optimization and machine learning 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 * 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 Basic Qualifications - Experience in any of the following areas: online optimization, control theory, ranking models, algorithms and data structures, parallel and distributed computing, - 10+ years of building models for business application experience - PhD in computer science, machine learning, statistics, mathematics, operations research, or a related field - Experience programming in Java, C++, Python or related language Preferred Qualifications - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Multiple years of experience working with large-scale, complex datasets to create/optimize machine learning, online optimization, ranking, simulation, and forecasting models. - Strong problem solving and analytical abilities - Experience with modeling tools such as scikit-learn, R, Spark MLlib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems - Proven experience leading the delivery of large-scale, high-quality systems - Experience working on automated marketing technologies - Experience working on advertising solutions. - Experience working with AWS Services, consuming, managing large scale datasets. - Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.