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Senior Economist, Manager, Prime Machine Learning and Economics

Job ID: 1830137 | Amazon.com Services LLC

DESCRIPTION

Job summary
Amazon Prime is looking for a talented Senior Economist Manager 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. At Amazon you will be working in one of the world's largest and most exciting big-data environments. The Senior Economist Manager role occupies a unique space at the intersection of technology, machine-learning, econometrics, large-scale scientific computing, social science, and product management.

As a Senior Economist Manager within Amazon Prime, you will manage a team of economists, applied scientists, and engineers, working closely with our world-class business and software development teams to propose and estimate novel statistical and econometric models to directly inform strategic decisions about characteristics of the Amazon Prime membership. These include what membership prices, benefits, and benefit content deliver the most value for our customers around the world. Your team will solve these problems using structural econometrics, causal inference, machine learning, and massively parallelized scientific computing, and work closely with our software development team to automate these models at scale in distributed computing infrastructures such as Apache Spark. 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 their own capacity for building, estimating, and defending causal statistical models using software such as R, Python, or STATA, with a willingness to learn causal inference and structural econometrics and creating production 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. Additionally, this candidate will show a track record of managing others to perform these tasks, creating a strategic vision for teams and managing team workflows, at-scale and on time. The role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.


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, visit https://www.amazon.jobs/en/disability/us


BASIC QUALIFICATIONS

· PhD in Economics or closely related field
· PhD in Economics
· Proven experience in building statistical models using R, Python, STATA, or a related software (especially, discrete choice modeling), with a willingness to learn and develop additional skills in causal inference, structural econometrics, machine learning, large-scale scientific / distributed computing.
· 2+ years of post-PhD experience

PREFERRED QUALIFICATIONS

· 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 utility-theory 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)
· experience managing high-performing science teams
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation




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.