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DESCRIPTION

Want to work in a start-up environment with the resources of Amazon behind you? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, passionate about machine learning, deep learning, big data systems, enjoy designing and implementing new features and machine learned models, and intrigued by ambiguous problems, look no further.

Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to 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 Kindles, tablets, and mobile devices. 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, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.

About Our Team:

Our team is responsible for building a new advertising product for non-endemic advertisers. We are tasked with taking this start-up offering to market, with the goal of empowering over one million non-endemic advertisers to independently plan and execute campaigns. “Non-endemic” brands offer products and services that are not sold/available in Amazon’s retail marketplace, including restaurants, hotels, airlines, insurance, telecom, and automobiles. We are embarking on a multi-year vision to democratize display advertising for non-endemic advertisers at self-service scale. This will open up Amazon Ads to self-service non-endemic demand— whether they sell on the Amazon store or not— to activate Amazon Ads first-party audiences built from shopping and streaming signals and access unique ad inventory to help grow their business.




Key job responsibilities
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new and innovative machine learning approaches.
- Train and fine-tune neural models including transformers and language models.
- Recruit Applied Scientists to the team and provide mentorship.