Amazon

DESCRIPTION

We're looking for an Applied Scientist to optimize prediction, ranking and bidding for Amazon's programmatic advertising product. In this role you will work at the forefront of high scale low latency customer-facing advertising systems, mixing machine learning, game theory and feedback control. Your work will affect multi-billion dollar businesses, and you will be responsible for designing, testing and delivering significant breakthrough's for Amazon's business.

Key job responsibilities

• Design and implement auctions for scaled self-serve display advertising.
• Own the allocation and pricing decision for hundreds of thousdands of candidate ads with diverse objectives across highly varied supply types.
• Invent new auction types and controls for advertisers that balance value for shoppers, advertisers and Amazon.
• Be immersed in Amazon's advertisers and their objectives, and think long-term about how to turn those objectives into products and technical capabilities
• Understand the latest literature on auction theory, machine learning and measurement to guide strategic investment for the organization

A day in the life

• Be immersed in Sponsored Display's auction data: candidate ads, objectives, bids and outcomes
• Design, prototype and validate new auction mechanisms or parameterizations
• Take technical leadership over turning prototypes into shopper- and advertiser-facing software
• Stay abreast of the latest trends and opportunities in machine learning, economics, auction theory and measurement
• Be an advocate and expert for SD's auction to leaders and stakeholders inside and outside advertising

About the team

Sponsored Display is a rapidly growing advertising product that aims to bring Display-style advertising to self-serve advertisers of any size. We're a customer-focused product powered by deep, exciting technology. We bias towards disruptive innovation that affects the experiences of all our advertisers and shoppers worldwide. We are deeply flexible in technology and methods, prefer multi-displicplinary collaborations and broad viewpoints, and are obsessed over cutting edge research in customer-facing software and products.

BASIC QUALIFICATIONS

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

• Experience using Unix/Linux
• Experience in professional software development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.