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Applied Scientist II, Advertising Incrementality Measurement
Amazon
On-siteseniorPosted May 6, 2026
About the Role
Develop and deploy novel scientific models using ML/DL and causal inference to measure advertising effectiveness, improve existing solutions, and guide business strategy.
Requirements
Expertise in ML/DL, AI, causal modeling, big-data analytics, and econometric modeling to develop and deploy advertising measurement solutions. Strong analytical and communication skills are essential.
Full Job Description
Do you want to lead the Ads industry and redefine how we measure the effectiveness of Amazon Ads business? Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be a science leader within our Advertising Incrementality Measurement science team!
Our work builds the foundations for providing customer-facing advertising measurement tools, furthering internal research & development, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions, and this role will play a key role in the release and expansion of these offerings.
We are looking for a thought leader that has an aptitude for delivering customer-focused solutions and who enjoys working on the intersection of Big-Data analytics, Machine/Deep Learning, and Causal Inference. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine learning and/or econometric modeling to solve business problems. You should have strong analytical and communication skills, be able to work with product managers to define key business questions and work with the engineering team to bring our solutions into production. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon advertising, and also allow you to become part of our large science community.
Key job responsibilities
• Apply expertise in ML/DL, AI, and causal modeling to develop new models that describe how advertising impacts customers’ actions
• Own the end-to-end development of novel scientific models that address the most pressing needs of our business stakeholders and help guide their future actions
• Improve upon and simplify our existing solutions and frameworks
• Review and audit modeling processes and results for other scientists, both junior and senior
• Work with leadership to align our scientific developments with the business strategy
• Identify new opportunities that are suggested by the data insights
• Bring a department-wide perspective into decision making
• Develop and document scientific research to be shared with the greater science community at Amazon
About the team
AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.
Our work builds the foundations for providing customer-facing advertising measurement tools, furthering internal research & development, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions, and this role will play a key role in the release and expansion of these offerings.
We are looking for a thought leader that has an aptitude for delivering customer-focused solutions and who enjoys working on the intersection of Big-Data analytics, Machine/Deep Learning, and Causal Inference. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine learning and/or econometric modeling to solve business problems. You should have strong analytical and communication skills, be able to work with product managers to define key business questions and work with the engineering team to bring our solutions into production. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon advertising, and also allow you to become part of our large science community.
Key job responsibilities
• Apply expertise in ML/DL, AI, and causal modeling to develop new models that describe how advertising impacts customers’ actions
• Own the end-to-end development of novel scientific models that address the most pressing needs of our business stakeholders and help guide their future actions
• Improve upon and simplify our existing solutions and frameworks
• Review and audit modeling processes and results for other scientists, both junior and senior
• Work with leadership to align our scientific developments with the business strategy
• Identify new opportunities that are suggested by the data insights
• Bring a department-wide perspective into decision making
• Develop and document scientific research to be shared with the greater science community at Amazon
About the team
AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.