Sr Applied Scientist, Sponsored Products and Brands

Job Description

Locations

• United States, NY, New York, New York, NY, United States

Salary

Salary not disclosed

Skills Required

• - PhD, or Master's degree and 6+ years of applied research experienceintermediate
• - 3+ years of building machine learning models for business application experienceintermediate
• - Experience programming in Java, C++, Python or related languageintermediate
• - Experience with neural deep learning methods and machine learningintermediate
• - Master's degree, or a PhD and experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NFintermediate

Required Qualifications

• - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
• - 3+ years of building machine learning models for business application experience (experience, 3 years)
• - Experience programming in Java, C++, Python or related language (experience)
• - Experience with neural deep learning methods and machine learning (experience)
• - Master's degree, or a PhD and experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF (experience)

Preferred Qualifications

• - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
• - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
• - Experience in auctions or mechanism design (experience)
• - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability (experience)
• Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)

Responsibilities

• • 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.
• About the team
• 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.

Documents

• Accommodations Information (web)
• https://www.aboutamazon.com/workplace/employee-benefits (web)

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