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Economist, Prime Machine Learning and Economics

Job ID: 2243846 | Services LLC


Job summary
Amazon Prime is looking for a talented Economist to help manage our ever growing information needs and support analysis of increasingly complex business questions. At Amazon Prime, understanding customer data is paramount to our success in providing customers with relevant and enticing benefits such as fast free shipping, instant videos and music, in an expanding number of international marketplaces. The Economist role occupies a unique space at the intersection of technology, machine-learning, econometrics, large-scale scientific computing, social science, and product management.

As an Economist within Amazon Prime, you will build a foundational econometrics used to help Prime plan company-wide investments in Prime. To do so, you will work closely with a team of structural and theoretical econometricians, applied and research scientists, and business and software development teams, along with Amazon Scholars (leading academic scientists from major universities). You will propose and estimate novel statistical and econometric models at the scientific frontier of time series statistics, structural econometrics, and machine learning. You will directly inform large-scale strategic decisions about how to improve the Prime membership, in partnership with senior scientific and business leaders. You will serve as a science leader across our worldwide science teams (now spanning pods within multiple marketplaces). You will utilize and enhance massively parallelized scientific computing paradigms, in partnership with our scientific software teams. This position is unique in its exposure to senior members of the Prime team and other Amazon business units.

The successful candidate will have demonstrated capacity for successfully building, estimating, and defending causal statistical models using software such as R, Python, Scala, or the equivalent, as well as how to create production-quality scientific software. Knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. The role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members. It can scale as both a large-scope individual contributor role, or as a manager role, depending on candidate skillset and career aspirations.

Location options for this position include Seattle, WA and Arlington, VA.


  • PhD in Economics or closely related field

  • Proven experience in building statistical models using R, Python, STATA, or a related software
  • At least one academic or industry publication utilizing time series forecasting
  • Experience with using large-scale scientific computing software, e.g. Spark


  • Proficiency in Spark-Scala or Py-Spark
  • Proven record of bringing high impact statistical models to production, at scale
  • Willingness to learn Spark-Scala and/or PySpark
  • Ability to work effectively within an interdisciplinary science team of economists, applied scientists, software engineers, and data engineers
  • Ability to communicate relevant scientific insights from data to senior business leaders, financial analysts, and product managers
  • Extensive theoretical statistical training, including the ability to carefully adapt/modify existing statistical tools to accommodate new applied use cases
  • Experience with empirical macro or finance-based time series forecasting; familiarity with utility-based discrete choice modeling
  • One or more publications in peer-reviewed statistical journals
  • Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)

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