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Amazon Principal Economist, Topline Forecasting in New York, New York

Description

Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today.

The Topline Forecasting team in the Supply Chain Optimization Technologies (SCOT) group is looking for innovative, passionate and results-oriented Principal Economist to provide thought-leadership to help answer these questions. You will have an opportunity to own the long-run outlook for Amazon’s global consumer business and shape strategic decisions at the highest level.

The successful candidate will be able to formalize problem definitions from ambiguous requirements, build econometric models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems.

Key job responsibilities

  • You understand the state-of-the-art in time series and econometric modeling.

  • You apply econometric tools and theory to solve business problems in a fast moving environment.

  • You excel at extracting insights and correct interpretations from data using advanced modeling techniques.

  • You communicate insights in a digestible manner to senior leaders in Finance and Operations within the company.

  • You are able to anticipate future business challenges and key questions, and have the ability to design modeling solutions to tackle them.

  • You have broad influence over the Topline team’s scientific research agenda and deliverables.

  • You contribute to the broader Econ research community in Amazon.

  • You advise other economists on scientific best-practices and raise the bar of research.

  • You will actively mentor other scientists and contribute to their career development.

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

Bellevue, WA, USA | New York, NY, USA

Basic Qualifications

  • PhD in Economics or closely related field.

  • Track record of publications that have advanced the state-of-the-art.

  • 6-8 or more years of experience in industry, consulting, government or academic research.

  • Expertise in applied time series.

  • Fluency in at least one statistical software package such as R, Stata, Matlab, SAS.

Preferred Qualifications

  • Strong background in econometrics, statistics methodology, machine learning, applications to business problems, and/or big data.

  • Experience with programming languages such as Python, Java, C++, experience with SQL and / or working in a Unix / Linux environment is a plus.

  • Ability to work in a fast-paced business environment.

  • Effective verbal and written communications skills.

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 $151,500/year in our lowest geographic market up to $294,700/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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