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DESCRIPTION

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth.

The Search Ranking and Interleaving (R&I) team within the Marketplace Intelligence org in SP is responsible for determining 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 ranking and allocation 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.

We are looking for an Applied Scientist to join the Search Ranking team in MI. The team is responsible for improving the quality of ads shown to users (e.g., relevance, personalized and contextualized ranking to improve shopper experience and business metrics) via online experimentation, ML modeling, simulation, and online feedback. As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset.


Key job responsibilities
- Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon.
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
- Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
- Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them
- Research new and innovative machine learning approaches.
- Recruit Scientists to the team and provide mentorship.