- Seattle, WA
Compensation Science is a fast-growing, interdisciplinary team working at the intersection of data science, economics, and product development. We are building analytic and predictive models from the ground up to surface actionable insights and scale pay for hundreds of thousands of Amazon employees worldwide.
We are looking for an outstanding data scientist with broad a methodological toolkit and experience working with different types of data sources (e.g. enterprise data, surveys, external sources) to transform compensation decision-making with science. This role will build and operationalize models that generate recommendations in new compensation products and automate insights that drive high-impact decisions.
• Own the development of new statistical/machine learning models to solve business problems
• Improve model inputs by onboarding new data sources and creating new metrics
• Assist in the delivery of automated, scalable analytic and predictive models
• Collaborate with economists, scientists, and engineers on the team and across the HR organization
• Interpret and communicate results to global business stakeholders
• Bachelor's Degree
• 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
• 2 years working as a Data Scientist
• MS/PhD training in a quantitative field such as Statistics, Computer Science, Applied Math, Economics
• 2+ years of experience working with a research/applied science team
• Highly proficient in causal inference, machine learning, or optimization
• Effective written and verbal communication
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