Compensation Science is building economic models and algorithms from the ground up to design and scale pay for hundreds of thousands of Amazon employees worldwide. This fast-growing, interdisciplinary team is working at the intersection of research, economics, machine learning, and product development. Our mission is to use science to assist and measurably improve every pay decision made at Amazon.
We are looking for a dynamic leader to join our leadership team. Reporting directly to the Director of Global Compensation and Benefits, you will lead a team of research scientists in improving the predictability, personalization, and performance of Amazon's compensation systems and practices. You will use your experience in modeling, statistics, and simulation to design models for new policies, simulate their performance, and evaluate their benefits and impacts to Amazon's ability to attract and retain the best talent in the world. Once built, you and team will partner closely with engineering teams to productize your models for scalable application.
This role is highly strategic and will interact with and present regularly to the most senior leaders in Human Resources. The ideal candidate will be entrepreneurial and innovative, thriving on solving challenging, ambiguous problems.
• Build and lead a high-performing team of world-class scientists;
• Manage compensation research projects through all stages: ideation, experiment design, data collection, modeling, evaluation, and communication of recommendations;
• Frame open-ended business objectives into actionable research plans;
• Work closely with software engineering teams to drive real-time model implementations and new feature creation;
• Balance scientific rigor and pragmatism, in order to deliver results at the speed of business decision-making;
• Build mechanisms to scale collaborations across science and analytics teams across the HR organization;
• Interpret and communicate research results and policy recommendations to global HR and business stakeholders.
• 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
• Experience working with with highly confidential employee data
• 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)
• Fluency working with technical teams
• Experience with AWS features (S3, Redshift)