• Full Time
  • Texas
Responsibilities include:
· 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 Company‘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 Company 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.

To apply for this job please visit orbiterrecruiting.com.