Selling Partner Support (SPS) strives to provide best-in class customer service to all Selling Partners selling on Amazon platform. Our service center associates play a central role in providing effective and efficient solutions to our Selling Partners. SPS is looking for a Senior Economist who will identify data-driven changes to help improve the productivity, career growth and retention of our service center associates, and subsequently positively impacting our Selling Partner’s experience. Senior Economist will be able to leverage large set of information on associate training data, their day-to-day work activities, associate interactions with supervisors and various performance metrics to draw causal inferences about associate behavior using machine learning (ML) techniques. Our economists build econometric models using our world class data systems, and apply economic theory to solve business problems in a fast-moving environment.
· Leverage ML techniques to develop causal inference models to identify key associate-supervisor interactions that improve Amazon associate productivity and retention as well as our Selling Partner satisfaction.
· Influence key business decisions in potentially adjusting labor plans, shift structures, compensation and/or benefits to increase Amazon's appeal across a diverse workforce.
· Work with SPS Applied Scientists, Economists and leadership to develop research roadmap.
· Identify and pitch new opportunities to leadership that are suggested by the data.
· Review and audit modeling processes and results for other scientists, both junior and senior.
· Partner with other science leaders throughout Amazon to develop consistent and repeatable solutions.
· Ph.D. degree in economics, labor economics, behavioral economics or related social science field with expertise in econometrics or applied statistics.
· Knowledge or experience of constructing, estimating, and defending causal statistical models.
· Ability to work effectively within an interdisciplinary science team of economists, applied scientists, software engineers, and data engineers.
· Experience of standard ML modeling techniques such as double-lasso, boosted regression trees and neural network.
· Knowledge of standard time series forecasting techniques such as ARIMAX, ETS.
· Proven track record in leading, mentoring and growing teams of scientists.
· Experience with people analytics at a regional or global scale.
· Experience with at least 1 scripting language such as Python, Scala, or R.
· Ability to apply advanced ML/statistical methods, and able to communicate effectively about these methods to non-technical audiences.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation