Economist, Ads Measurement Science
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
- 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)
- Deep expertise in causal inference, with articles published in peer-reviewed econometrics journals.
- Proficiency in Python or a related programming language.
PREFERRED QUALIFICATIONS
- Experience with handling of large datasets
- Experience in the advertising industry or closely related problems.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.