Sr. Manager, Applied Science, Sponsored Products and Brands
Amazon (AI roles) · New York, New York, USA
No salary listed. Estimated from 297 salary-disclosed Marketing roles on this board: $163K–$227K (interquartile range; estimate, not the employer's figure).
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About Sponsored Products and Brands
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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.
About our team
The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions.
Key job responsibilities
Responsibilities:
- Lead science and engineering needs across ad systems and models that power sponsored products ads for offsite shopping experiences
- Surface qualitative and quantitative insights as the voice of the advertisers to shape product direction and ensure product-market fit
- Scale ad product adoption across advertisers, agencies, and tool providers
- Collaborate with product, science, and engineering teams across SPB and ads to make the right trade-off decisions to build, partner, or build together to scale shopping experiences offsite.
Your contributions will be highly visible and instrumental in hitting goals carried by Amazon's leadership team (S-Team). A diverse group of stakeholders will rely on your vision and messaging, including advertisers, agencies, and internal ad sales and operations teams. - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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.
About our team
The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions.
Key job responsibilities
Responsibilities:
- Lead science and engineering needs across ad systems and models that power sponsored products ads for offsite shopping experiences
- Surface qualitative and quantitative insights as the voice of the advertisers to shape product direction and ensure product-market fit
- Scale ad product adoption across advertisers, agencies, and tool providers
- Collaborate with product, science, and engineering teams across SPB and ads to make the right trade-off decisions to build, partner, or build together to scale shopping experiences offsite.
Your contributions will be highly visible and instrumental in hitting goals carried by Amazon's leadership team (S-Team). A diverse group of stakeholders will rely on your vision and messaging, including advertisers, agencies, and internal ad sales and operations teams. - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
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