The People eXperience and Technology (PXT) Central Science Team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms, process improvements and products, which simultaneously improve Amazon and the lives, wellbeing, and the value of work of Amazonians. We are an interdisciplinary team which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We invest in innovation and rapid prototyping of scientific models, AI/ML technologies and software solutions to accelerate informed, accurate, and reliable decision backed by science and data. As a research scientist you will you will design and carry out surveys to address business questions; analyze survey and other forms of data with regression models; perform weighting and multiple imputation to reduce bias due to nonresponse. You will conduct methodological and statistical research to understand the quality of survey data. You will work with economists, engineers, and computer scientists to select samples, draft and test survey questions, calculate nonresponse adjusted weights, and estimate regression models on large scale data. You will evaluate, diagnose, understand, and surface drivers and moderators for key research streams, including (but are not limited to) attrition, engagement, productivity, inclusion, and Amazon culture.

Key job responsibilities
- Execute a scalable global content development and validation strategy to drive more effective decisions and improve the employee experience across all of Amazon
- Conduct psychometric and econometric analyses to evaluate integrity and practical application of survey questions and data
- Identify and execute research streams to evaluate how to mitigate or remove sources of measurement error
- Partner closely and drive effective collaborations across multi-disciplinary research and product teams
- Manage full life cycle of large-scale research programs (Develop strategy, gather requirements, manage and execute)
- 2+ years of PhD-level coursework in statistics
- Experience applying scientific principles and concepts to business problems and products
- Experience with data analysis packages (R, Stata, Python, etc.)
- Experience using SQL databases to manage and analyze large data sets