Mgr, Compensation Applied Science
- Seattle, WA
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 small team of machine learning scientists and data engineers in building a new ML concept for Amazon's compensation system from the ground up. 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 progress 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 team of world-class scientists to deliver machine-learning solutions from ideation, exploration, to production. Provide technical and career development guidance to scientists in the organization.
• Manage the design, development and evaluation of highly innovative, scalable models and algorithms. Develop science roadmap and run sprints;
• Work with product and software engineering teams to manage the integration of successful models and algorithms in complex, real-time production systems at very large scale;
• Foster cross-team collaboration with other science, product, UX, and tech partners;
• Analyze and convey impact and results to senior management and stakeholders
• MS or PhD in Computer Science, Machine Learning, AI, Statistics, or other related fields
• 5+ years of practical experience applying ML to solve complex problems for large-scale applications;
• Proficiency in Python, and modern ML frameworks
• Understanding of computer science fundamentals such as data structures, object-oriented design and service-oriented architectures
• Ability to convey Machine Learning concepts and considerations to all levels of the organization
• 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 managing machine learning teams,with a strong track record of hiring and leading experienced scientists as well as a successful record of developing junior members from academia/industry to a successful career track;
• Significant peer reviewed scientific contributions in relevant field
• Experience defining organizational research and development practices in industry
• Experience with adverse impact testing in statistical analysis
• Experience with bias identification/remediation in Machine Learning and Artificial Intelligence systems
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