Amazon
Senior Economist, Amazon
Amazon, Bellevue, Washington, us, 98009
Job ID: 2845562 | Amazon.com Services LLC
Amazon Stores Ads Science team is looking for a Senior Economist to help translate cutting-edge econometrics and machine learning research into production solutions. The individual will have the opportunity to shape the technical and strategic vision of a highly ambiguous problem space at the intersection of Amazon’s Stores and Advertising businesses, and deliver measurable business impacts via cross-team and cross-functional collaboration.
Amazon is investing heavily in building a world-class advertising business. Our advertising products are strategically important to Amazon’s Retail and Marketplace businesses for driving the long-term growth. The mission of the Stores Ads Science team is to identify opportunities to jointly optimize Amazon’s Stores and Advertising business, by enhancing the usage of advertising signals in Stores’ decision-making and vice versa to drive the long-term economic value to shoppers, sellers/vendors, and Amazon. Some of our work includes measuring ads impact and shopping content incrementality to improve shopper experience, developing the science of explaining seller/vendor inter-related decisions between Stores and Ads (e.g.: pricing, Sponsored Ads participation) to optimize fees and incentives, and making Stores’ traffic acquisition strategies aware of shoppers’ and advertisers’ onsite advertising behavior.
We partner closely with tech and product teams across Stores and Advertising, and are constantly advancing experimentation methodology to accelerate science development and quantify business impacts. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action.
Key job responsibilities - Function as a technical lead to shape the strategic vision and the science roadmap of a highly ambiguous problem space - Develop economic theory and deliver econometrics and machine learning models to unlock the new opportunities for jointly optimizing sellers’/vendors’ decision-making between Stores and Ads - Design, execute, and analyze experiments to verify the efficacy of different scientific solutions in production - Partner with cross-team technical contributors (scientists, software engineers, product managers) to implement the solution in production - Write effective business narratives and scientific papers to communicate to both business and technical audiences, including the most senior leaders in the company BASIC QUALIFICATIONS
- PhD in economics or equivalent PREFERRED QUALIFICATIONS
- Experience in building analytic or scientific data products or solutions - Experience in econometrics (e.g., program evaluation, forecasting, time series, panel data, or high dimensional problems), economic theory, and quantitative methods - Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks) - Experience in building statistical models using R, Python, STATA, or a related software 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.
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Amazon is investing heavily in building a world-class advertising business. Our advertising products are strategically important to Amazon’s Retail and Marketplace businesses for driving the long-term growth. The mission of the Stores Ads Science team is to identify opportunities to jointly optimize Amazon’s Stores and Advertising business, by enhancing the usage of advertising signals in Stores’ decision-making and vice versa to drive the long-term economic value to shoppers, sellers/vendors, and Amazon. Some of our work includes measuring ads impact and shopping content incrementality to improve shopper experience, developing the science of explaining seller/vendor inter-related decisions between Stores and Ads (e.g.: pricing, Sponsored Ads participation) to optimize fees and incentives, and making Stores’ traffic acquisition strategies aware of shoppers’ and advertisers’ onsite advertising behavior.
We partner closely with tech and product teams across Stores and Advertising, and are constantly advancing experimentation methodology to accelerate science development and quantify business impacts. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action.
Key job responsibilities - Function as a technical lead to shape the strategic vision and the science roadmap of a highly ambiguous problem space - Develop economic theory and deliver econometrics and machine learning models to unlock the new opportunities for jointly optimizing sellers’/vendors’ decision-making between Stores and Ads - Design, execute, and analyze experiments to verify the efficacy of different scientific solutions in production - Partner with cross-team technical contributors (scientists, software engineers, product managers) to implement the solution in production - Write effective business narratives and scientific papers to communicate to both business and technical audiences, including the most senior leaders in the company BASIC QUALIFICATIONS
- PhD in economics or equivalent PREFERRED QUALIFICATIONS
- Experience in building analytic or scientific data products or solutions - Experience in econometrics (e.g., program evaluation, forecasting, time series, panel data, or high dimensional problems), economic theory, and quantitative methods - Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks) - Experience in building statistical models using R, Python, STATA, or a related software 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.
#J-18808-Ljbffr