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/DNN raising the science bar and connecting leading-edge science research to Amazon-scale implementation If so come join Amazon Ads to be an Economist leader within our Advertising Incrementality Measurement science team!

Our work builds the foundations for providing customer-facing experimentation tools furthering internal research & development on Econometrics and building out Amazons 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.

Key job responsibilities
As an Economist leader within the Advertising Incrementality Measurement (AIM) science team you are responsible for defining and executing on key workstreams within our overall causal measurement science particular you can lead the development of experimental methodologies to measure ad effectiveness and also build observational models that lay the foundations for understanding the impact of individual ad touchpoints for billions of daily ad interactions. You will work on a team of Applied Scientists Economists and Data Scientists alongside a dedicated Engineering team to work backwards from customer needs and translate product ideas into concrete science deliverables. You will be a thought leader for inventing scalable causal measurement solutions that support highly accurate and actionable insights--from defining and executing hundreds of thousands of RCTs to developing an exciting science R&D agenda. You will be working with massive data and industry-leading partner scientists while also interfacing with leadership to define our future vision. Your work will help shape the future of Amazon Advertising.

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.

- PhD in economics or equivalent

- Experience in analytics and applied economics
- Experience in developing and executing an analytic vision to solve business-relevant problems
- Experience in building statistical models using R Python STATA or a related software
- Experience in industry consulting government or academic research

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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at NY New York - 175100.00 - 236900.00 USD annually

Required Experience:

Senior IC

Job Tags

Full time, Flexible hours

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