Research Scientist

Job ID: 1520547 | Canary - US


Global Talent Management (GTM) Science is an innovative organization that exists to propel Amazon HR towards being the most scientific HR organization on earth. The GTM Science mission is to use Science to assist and measurably improve every talent decision made at Amazon. We do this by discovering signals in workforce data, deploying statistical models into Amazon’s talent products, and guiding the broader GTM team to pursue high-impact opportunities with tangible returns. This multi-disciplinary approach spans capabilities, including: data engineering, reporting and analytics, research and behavioral sciences, and applied sciences such as economics and machine learning.

We are seeking a Research Scientist with expertise in mixed-methods research in social science, public health, or similar research, including development and evaluation of theoretical frameworks, qualitative data collection and analysis methods in a variety of settings (e.g. focus groups, field studies, surveys, observational studies, “found data”, quantitative analytics), and statistics. The ideal candidate will be equally comfortable with qualitative and quantitative methods, though candidates with greater exposure to and familiarity with qualitative methods will be considered if a solid understanding of the quantitative methods described above exists. This person will possess strong experience with managing project deliverables for diverse stakeholders and thrive in a fast paced work environment. In this role you will:
· Design, develop, and execute quantitative and qualitative data collection methods in Future of Work (FoW), Diversity Equity & Inclusion (DEI), and related talent management efforts
· Conduct quantitative analyses of talent management data and trends
· Conduct qualitative data collection and analysis
· Partner closely and drive effective collaborations across multi-disciplinary research and product teams
· Consult on appropriate analytic methodologies and scope research requests


Basic qualifications
· PhD in Quantitative Methods, Quantitative Policy Analysis, Assessment & Measurement, IO Psychology, or equivalent Master's degree plus 1+ years of research experience in a quantitative field
· 2 years of experience conducting end-to-end scientific research in an applied setting
· Strong programming skills in at least one statistics program (R, SAS, Stata, Python, SPSS)
· Excellent written and verbal communication skills for both technical and non-technical audiences
· Experience partnering with engineers and tech to implement science solutions into product
· Strong organizational skills, time management, and program management skills


Preferred qualifications
· 5 years of relevant experience described above
· Experience conducting DEI related research in a applied setting using experimental research methodology and survey methodology
· Advanced Statistics (Factor Analysis, Item Analysis, Adverse Impact Analysis, IRT, Regressions, MLM, SEM, HLM)
· Proficiency in R and SQL
· Experience using data to drive Talent Management Solutions
· Adaptable, creative, and thrives in a fast-paced work environment