The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
• Collaborate with business, engineering and science leaders to establish science optimization and monetization roadmap for Amazon Retail Ad Service
• Drive alignment across organizations for science, engineering and product strategy to achieve business goals
• Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon advertisers and third party retailers
• Develop state of the art experimental approaches and ML models to keep up with our growing needs and diverse set of customers.
• Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done.
Amazon Retail Ad Service within Sponsored Products and Brands is an ad-tech solution that enables retailers to monetize their online web and app traffic by displaying contextually relevant sponsored products ads.
Our mission is to provide retailers with ad-solution for every type of supply to meet their advertising goals. At the same time, enable advertisers to manage their demand across multiple supplies (Amazon, offsite, third-party retailers) leveraging tools they are already familiar with. Our problem space is challenging and exciting in terms of different traffic patterns, varying product catalogs based on retailer industry and their shopper behaviors.