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Amazon Senior Economist, Compensation Science in Seattle, Washington

Description

The Central Science team within the People Experience and Technology organization is building economic models and algorithms from the ground up to design and scale pay for hundreds of thousands of Amazon employees worldwide. The fast-growing, interdisciplinary team is working at the intersection of economics, machine learning, and product development.

We are looking for an Economist who will provide structure to ambiguous and complex business problems, develop solutions to these problems using economics, econometrics, machine learning and other scientific approaches, work with engineers to scale and launch science models in product, and initiate high impact projects in the compensation space. A successful candidate will be able to partner effectively with both business and technical teams, including clear communication of results and the ability to influence a variety of stakeholders.

Economists at Amazon have access to engineering and econometric/machine learning tools and opportunities to learn new methods from world-class scholars.

Responsibilities:

  • Own the development of economic models and econometric analyses

  • Assist in the delivery of automated, scalable analytic models

  • Work collaboratively with economists, scientists, and engineers on the team and across the organization

  • Interpret and communicate results to global business stakeholders

About the team

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

We are open to hiring candidates to work out of one of the following locations:

Arlington, VA, USA | Boston, MA, USA | Chicago, IL, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Simi Valley, CA, USA

Basic Qualifications

  • PhD in economics or equivalent

Preferred Qualifications

  • 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 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.

Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/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.

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