Global Talent Management (GTM) is a central Human Resource (HR) team responsible for creating and evolving Amazon’s human capital and talent products and processes. The GTM Science team is a growing interdisciplinary team within GTM that develops evidence-based products and services that power the growth and development of Amazon’s talent across all of our businesses and locations around the world.
GTM Science exists to propel GTM and Amazon HR toward being the most scientific HR organization on earth. Our 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, integrating those signals and behavioral recommendations into Amazon’s talent products, and helping Amazonians make high-judgement decisions that raise the bar on talent. Our multi-disciplinary approach covers an array of capabilities, including: data engineering, business intelligence and analytics, research and behavioral sciences, data science, and applied sciences such as economics and machine learning.
We are looking for a dynamic leader to join our leadership team. Reporting directly to the Director of GTM Science, you will lead a team of researchers and analysts primarily responsible for handling high-priority senior-leadership research requests that require scientific rigor and agility. You will be responsible for building mechanisms to scale collaborations across all areas of GTM Science/Product/Tech and to build project-based partnerships with HR Line Analytics and COE teams. Your approach balances scientific rigor and pragmatism, in order to deliver results at the speed of business decision-making. You and your team thrive on quickly framing open-ended business requests into an actionable research plan and reporting your results to the highest levels of leadership, to meaningfully shape Talent processes, policies, and programs in areas such as: Diversity & Inclusion, Flexible Work, Talent Mobility, Talent Evaluation, Talent Retention, Performance Management.
· Master’s degree or PhD in Quantitative Behavioral Sciences field, Economics, Statistics, Math, Engineering, Computer Science, or related applied research field
· 7+ years of experience applying research science methods and statistical models to solve large-scale organizational problems
· 5+ years managing research scientist teams and influencing VP/SVP/C-level leadership stakeholders
· Proficient with mixed methods research approaches (e.g. qualitative cognitive interviews + regression analysis) in the creation of time-bound research plans intended for rapid results
· Experience with organizational and team-level multivariate statistical analysis
· Proficient with Python, R, or SPSS for exploratory data analysis, statistical analysis, and predictive modeling
· Exceptional technical writing and communication skills for non-technical audience understanding of research results
· Highly adaptable, scrappy, creative, and thrives in a fast-paced and agile work environment
· Master's degree or PhD in Industrial and Organizational Psychology, Applied Experimental Psychology, Quantitative Psychology or related field
· Experience with adverse impact testing in statistical analysis
· Experience with bias identification/remediation in Machine Learning and Artificial Intelligence systems
· Proficiency in a least one area of Machine Learning (Regression, Classification, Clustering, Anomaly Detection, NLP)