Principal Research Scientist

3+ months agoArlington, VA


Are you passionate about conducting measurement research and experiments to assess and evaluate talent? Would you like to lead a research team and see your research in products that will drive key behaviors at scale to improve the employee experience and raise the bar of talent at Amazon? If so, you should consider joining the Global Talent Management (GTM) Science Organization.

Amazon 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 principle lead scientist with deep quantitative expertise developing assessment and validating measures (assessments, performance evaluations, and surveys) to lead a team to evaluate talent at Amazon. This person will possess knowledge of different measurement approaches to evaluate performance, a strong psychometrics background, scientific survey methodology, validation, adverse impact analysis, and experience developing legally defensible talent evaluation programs. In this role you will:

• Lead a team and develop a global research strategy and program on how to more effectively evaluate talent
• Conduct and oversee psychometrics analyses to evaluate integrity and practical application of different methods
• Develop and iterate on testing, experimenting, and evaluating content prior to global launch
• Identify 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


• MA in Quantitative Methods, Quantitative Policy Analysis, Assessment & Measurement, IO Psych, or other related field
• 7+ years of experience developing assessment and performance evaluations
• Advanced Statistics (Factor Analysis, Item Analysis, Adverse Impact Analysis, IRT, Regressions, MLM, SEM, HLM)
• Strong programming skills in at least one statistics program (R, SAS, Stata, Python, SPSS)
• Proficiency managing, merging, and manipulating large datasets
• Proficient communications (written and verbal) of technical information for non-technical audience
• Experience partnering with engineers and tech to implement science solutions into product
• Strong organizational skills, time management, and program management skills


• PhD in Quantitative Methods, Quantitative Policy Analysis, Assessment & Measurement, IO Psychology, or other related field
• > 10 years of relevant experience described above
• Experience leading, managing, and developing science teams
• Proficiency in R and SQL
• Deep expertise in legal defensibility of assessment and performance evaluation
• Experimental Research Methodology and Survey methodology
• Proficiency leading complex (beginning to end) research projects with multiple stakeholders
• Proven experience providing thought leadership and consultation to educate and influence key stakeholders
• Experience using data to drive Talent Management Solutions
• Experience demonstrating the down-stream business impact of research recommendations
• Adaptable, creative, and thrives in a fast-paced work environment

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

Job ID: Amazon-1391408