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Home›Jobs›Amazon›Senior Applied Scientist, Sponsored Products and Brands
Amazon

About Amazon

The everything store and cloud computing leader

🏢 Tech👥 1001+ employees📅 Founded 1995📍 South Lake Union, Seattle, WA⭐ 3.7
B2CB2BMarketplaceCloud ComputingeCommerce

Key Highlights

  • Headquartered in South Lake Union, Seattle, WA
  • Over 1.5 million employees worldwide
  • Leading cloud services through Amazon Web Services (AWS)
  • Acquired Whole Foods, Twitch, and Ring

Amazon, headquartered in South Lake Union, Seattle, WA, is the world's largest online retailer and a leader in cloud computing through Amazon Web Services (AWS). With over 1.5 million employees globally, Amazon operates in various sectors, including AI with its Alexa devices and a vast marketplace k...

🎁 Benefits

Amazon offers competitive salaries, stock options, generous PTO policies, and comprehensive health benefits. Employees also have access to a learning ...

🌟 Culture

Amazon's culture is driven by customer obsession and a focus on innovation. The company encourages employees to think big and move fast, fostering an ...

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Amazon

Senior Applied Scientist, Sponsored Products and Brands

Amazon • New York, New York, USA

Posted 6 months ago🏛️ On-SiteSeniorApplied scientist📍 New york
Apply Now →

Job Description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. 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 organization'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. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

As the detail page, homepage, and other Stores touchpoints continue to evolve, the Sponsored Products (SP) Off-Search organization is focused on building delightful ad experiences across these surfaces to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences (multi-persona), scales across diverse page types such as the homepage, detail page, and store-in-store surfaces (multi-surface), stays relevant to seasonal and event-driven moments (multi-moment), and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options (multi-intent). To execute this vision, we work closely with Stores stakeholders, spearhead the expansion of SP across Amazon-owned and operated pages, develop advanced ML and GenAI/LLM models, engineering systems, Tier-1 services, to optimize end-to-end ads flow from sourcing, auction to frontend customer experiences.

We are looking for a passionate Senior Applied Scientist who has technical expertise in information retrieval, Natural Language Processing (NLP), Large Language Models (LLM), Online Advertising, and/or randomized experiments. In addition to having hands-on experience in building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show willingness to continuously learn about new scientific approaches, and enjoy operating in startup-like environment.

Key job responsibilities
• Lead business, science and engineering strategy and roadmap for Sponsored Products Off-Search Sourcing and Relevance.
• Drive alignment across teams 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 and advertisers
• Develop state of the art experimental approaches and ML models.- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- 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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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.

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