Applied Science Manager, Stores-Ads Science

Amazon; Seattle (WA); On-site; USD 120,000 - 160,000; Full time

Job summary

Amazon seeks an Applied Science Manager for its Stores-Ads Science team in Seattle. The role involves leading the Ads Impact initiative to understand how advertising creates value for shoppers and partners, integrating AI with economics.

The ideal candidate will have a PhD and deep expertise in causal inference. Responsibilities include designing experiments, leading a team, and communicating findings to leadership. Join us to drive the future of advertising at Amazon.

Qualifications

• Deep expertise in causal inference and experimental design.
• Strong applied ML skills.
• Experience in leading scientific research.

Responsibilities

• Lead a team of scientists to optimize advertising value.
• Design experiments to measure causal mechanisms of ads.
• Communicate findings to senior leadership.

Skills

Causal inference

Experimental design

Applied machine learning

Education

PhD in relevant field

Job description

Applied Science Manager

Amazon's Stores-Ads Science team operates at the intersection of Amazon's Stores and advertising businesses. We develop causal measurement systems, optimization algorithms, and machine learning models that inform how advertising affects shopper engagement, driving selling partner growth and marketplace economics. Our science shapes decisions both at the strategic level and in production systems. We are a team of interdisciplinary scientists who combine causal inference, economic modeling, and machine learning to drive measurable business impact.

We are looking for an Applied Science Manager to lead our Ads Impact initiative. This team owns the science of understanding and optimizing how advertising creates value for shoppers and selling partners. What makes this role distinctive is its position at the frontier of AI and Economics: as Amazon's shopping experience evolves from traditional search toward LLM-powered, agentic commerce, the fundamental mechanisms through which advertising creates value are changing. This role will partner with leading scientists and academic researchers to measure these effects through large-scale causal experimentation, and develop novel methods to encode causal and economic reasoning into AI systems that optimize the shopping experience.

Key job responsibilities include leading a team of scientists, setting the technical vision and science roadmap for ads impact measurement and optimization. You will design experiments that identify the causal mechanisms through which advertising drives shopper engagement, advertiser value, and marketplace outcomes. You will develop optimization algorithms that integrate these causal signals into production and business decision-making, in close partnership with engineering and product teams across the organization. You will lead the research and communicate findings and recommendations to senior leadership through written narratives that connect technical science to business strategy.

This role requires deep expertise in causal inference and experimental design, combined with strong applied ML skills and the engineering judgment to translate research into production systems. You will hire and develop future science leaders, think strategically, set ambitious roadmaps in highly ambiguous problem spaces, and foster a culture that values both intellectual depth and production impact. You will work cross-functionally, influencing across organizational boundaries to drive alignment on complex, multi-sided tradeoffs.