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DESCRIPTION

Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities.

The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team.

Key job responsibilities
As a Applied Scientist II, you will:

* Conduct hands-on data analysis, build large-scale machine-learning models and pipelines
* Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production
* Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management
* Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
* Provide technical leadership, research new machine learning approaches to drive continued scientific innovation
* Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences