Sr. Applied Science Manager, Amazon Advertising - Sponsored Products & Brands, Conversational Ad Experiences

Sr. Applied Science Manager

Amazon Advertising is one of Amazon's 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 and Brands (SPB) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. 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!

The Sr. Applied Science Manager in this position will lead an organization focused on designing, developing, and launching innovative ad experiences delivered to shoppers in conversational contexts and AI agentic applications. The team utilizes leading-edge science and engineering technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational interfaces. These solutions also empower advertisers to reach shoppers, using their own voice to explain how their products meet shoppers' needs. The team collaborates with various teams across multiple Amazon organizations to push the boundary of what's possible in these fields.

Key job responsibilities:

• Drive transformative GenAI-based innovation for conversational and agentic ad experiences.
• Lead a cross-functional team of talented engineers, scientists, and product managers.
• Deliver these experiences for shoppers and advertisers.
• Play a critical role in elevating the team's scientific and technical rigor.
• Identify and implement best-in-class algorithms, methodologies, and infrastructure.
• Establish a long-term vision for continued scientific innovation.
• Set strategic goals to future-proof the organization's technical stacks and ML/LLM frameworks.
• Support new and emerging business objectives.
• Grow talents, fostering a culture of excellence and continuous learning.
• Enhance the organization's ability to solve complex problems.