Do you ever struggle to explain your work? How's this: "Do you shop at Amazon?” Every day, tens of millions of customers visit Amazon to discover, research, and buy products. Millions of interactions are processed each hour, as customers navigate and explore our vast selection of products, features, and services around the world. The Amazon Stores Ads Monetization Team’s vision is to enable customers to discover products they love from brand owners around the world. Amazon Stores are the product showroom for the “everything store”, our reach and impact uniquely positions us to innovate on behalf of our customers. The The Amazon Stores Ads Monetization Team’s partners with organizations across Amazon to drive high-quality advertising experiences across geographies, intents, missions, products and businesses; while ensuring a cohesive, lovable shopping experience.
We are looking for a Principal Applied Scientist to drive the development signals to optimally blend sponsored and organic recommendations on the site. You will work with science and business leaders from Shopping and Advertising to build Machine Learning (ML) models to determine when, where, and how many ads to show depending on customer characteristics and shopping missions. You will partner with product managers, other scientists, and software engineers to implement your ideas at scale.
Key job responsibilities
- Partner with teams in Shopping and Ads Amazon to develop signals that let ads program know when and where to serve ads on the Amazon site
- Develop ML models to improve ads monetization decisions in Amazon Stores, allowing us to personalize experiences depending on customer characteristics and shopping missions
- Collaborate with product managers, scientists, economists, and software developers to incorporate models in production systems
- Act as the machine learning authority for the Amazon Stores Advertising team with Amazon senior leaders and other science organizations
- Help craft the multi-year science strategy for the organization
About the team
This role is within a brand-new organization focused on delighting customers while driving revenue. Prospective candidates should have the desire and capability to drive results from the ’ground floor’ of an impactful and important charter.- 5+ years of hands-on work in predictive modeling and analysis experience
- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- Experience working in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python or related language
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment- 10+ years of relevant work in industry or academia experience
- Experience creating novel algorithms and advancing the state of the art
- Experience in online advertising
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 $179,000/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.
