offres d’emploi chez Amazon à United States

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Location: London, United Kingdom

Job Category: Other

EU work permit required: Yes

Job Reference: d9c8c335b33f

Job Views: 3

Posted: 17.05.2025

Expiry Date: 01.07.2025

We're looking for an Applied Scientist to optimize prediction, ranking, and bidding for Amazon's programmatic advertising product. In this role, you will work at the forefront of high-scale, low-latency customer-facing advertising systems, mixing machine learning, game theory, and feedback control. Your work will impact multi-billion dollar businesses, and you will be responsible for designing, testing, and delivering significant breakthroughs for Amazon's business.

1. Design and implement auctions for scaled self-serve display advertising.
2. Own the allocation and pricing decisions for hundreds of thousands of candidate ads with diverse objectives across highly varied supply types.
3. Invent new auction types and controls for advertisers that balance value for shoppers, advertisers, and Amazon.
4. Understand Amazon's advertisers and their objectives, and think long-term about turning those objectives into products and technical capabilities.
5. Stay informed on the latest literature on auction theory, machine learning, and measurement to guide strategic investments.

1. Analyze Sponsored Display's auction data: candidate ads, objectives, bids, and outcomes.
2. Design, prototype, and validate new auction mechanisms or parameterizations.
3. Lead the development of prototypes into shopper- and advertiser-facing software.
4. Keep up with trends and opportunities in machine learning, economics, auction theory, and measurement.
5. Advocate for and explain SD's auction strategies to leaders and stakeholders.

Sponsored Display is a rapidly growing advertising product aiming to bring display-style advertising to self-serve advertisers of all sizes. We focus on customer-centric products powered by advanced technology, emphasizing disruptive innovation, multidisciplinary collaboration, and cutting-edge research in customer-facing software and products.

• Master's degree
• Experience programming in Java, C++, Python, or related languages
• Experience with neural deep learning methods and machine learning
• Experience in building machine learning models for business applications
• Experience in applied research

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy, etc.
• Experience with large-scale distributed systems such as Hadoop, Spark, etc.