Amazon

Economist, Ads Measurement Science

Amazon  •  New York City, NY (Onsite)  •  2 hours ago
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Job Description

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision.

We are hiring an Economist on the team to develop the next generation of incrementality measurement products, capturing the effect of advertising in driving sales as well as the effects of measurement tools on advertiser engagement with Amazon. As an Economist on the team, you will lead the design, implementation, and validation of large-scale causal inference methodologies to capture these properties. You will communicate your results with science and business leaders, and partner with other scientists and engineers to carry solutions into production.

Key job responsibilities
Leverage deep expertise in causal inference to develop robust, causally grounded ads measurement solutions
Disambiguate problems to propose clear evaluation frameworks and success criteria
Work autonomously and write high quality technical documents
Partner closely with other scientists to deliver large, multi-faceted technical projects
Share and publish works with the broader scientific community through meetings and conferences
Communicate clearly to both technical and non-technical audiences and leaders
Contribute new ideas that shape the direction of the team's work
Mentor more junior scientists and participate in the hiring process

Basic Qualifications


- PhD in economics or equivalent

Preferred Qualifications

- 2+ years of industry, consulting, government, or academic research experience
- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)
- Experience in any of the following areas of applied economics (multiple areas preferred): reduced-form causal analysis, predictive modeling and causal ML algorithms, forecasting, hazard models, health and insurance economics, education economics, labor economics, and behavioral economics, designing and administering large-scale social science survey
- Knowledge of and proficiency in the use of Python scripting language
- Experience in the advertising industry or closely related problems.

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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About Amazon

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one.

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Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind.

You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.

Industry
IT & Software
Company Size
10,000+ employees
Headquarters
Seattle, WA
Year Founded
Unknown
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