Additional Information
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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.
We are the Sponsored Products - Marketplace Intelligence (MI) team. We are looking for an Applied Scientist to help build production ML and bandit solutions to customize the search experience. We determine which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers', advertisers', and Amazon's interests. To do this, we apply a broad range of machine learning, causal inference, and optimization techniques to continuously explore, learn, and optimize the allocation and ranking of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them.
You will be on the Search Ad Ranking and Interleaving team org - specifically the team that focusses on whole page optimization. Our mission is to personalize and contextualize SP ad allocation on the entire search page. We do this by modeling shopper responses to the number, placement, and quality of ads. We are a data- and hypothesis-driven organization that uses online experimentation, simulation, causal modeling, and online feedback to place ads where they're useful to shoppers and provide improved discoverability and sales for advertisers. This is a unique opportunity for someone who wants to have broad business impact, a direct impact on customers and the search experience, and get broad exposure to a wide range of scientific techniques (machine learning, bandit learning, optimization, LLMs).
We are looking for an Applied Scientist to join Interleaving team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. We'd like someone with practical experience with LLMs / GenAI for production to improve how we rank and allocate ads on the page today. If you thrive in a product-focussed and data-driven environment, then this role is for you. As a Applied Scientist on this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, product managers, software engineers and TPMs. You will have opportunity to design, run and analyze / experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation.
Key job responsibilities
* Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon.
* Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
* Develop efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace then evolve them
* Be an expert at designing and implementing solutions that use a range of data science methodologies to automate data analysis or to solve complex business problems.
* Perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experience, without compromising Ad revenue in addition to designing metrics for complex systems.
* Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity.
* Run A/B experiments, gather data, and perform statistical analysis.
Amazon.com · Seattle, WA