DESCRIPTION

The Selling Partner Fees team owns the end-to-end fees experience for two million active third party sellers. We own the fee strategy, fee seller experience, fee accuracy and integrity, fee science and analytics, and we provide scalable technology to monetize all services available to third-party sellers.

We are looking for an experienced Science manager to lead a team of machine learning scientists and economists to improve our understanding of seller economics, and enhance our ability to estimate the causal impact of fee, and policy changes. In this role you will provide technical guidance to scientists to develop machine learning and econometric models to influence our fee pricing models worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments where possible, or observational data when it is not. You will own the research agenda and prioritization for the team, and ensure that projects address the business needs.

The ideal candidate will have outstanding communication skills, strong technical knowledge, proven ability to lead a team scientists, and an innate drive to deliver results. He/she will be comfortable with ambiguity and will enjoy working in a fast-paced environment. He/she will work closely with Economists, Data / Applied Scientists, Strategy Analysts, and Software Developers.

Responsibilities:
• Lead a team of 10+ people across technical job families (Applied Scientists, Data Scientists, Economists, Data Engineers...).
• Manage a research agenda that balances short term deliverables with measurable business impact with long term, high risk / high reward projects.
• Stay up to date with recent scientific publications relevant to the team
• Provide technical and scientific guidance to team members
• Hire and develop top talent
• Collaborate with business and software teams both within and outside of fees for prioritization and resources

BASIC QUALIFICATIONS

• M.S. or PhD in Statistics, Machine Learning, Economics, Operations Research or similar field.
• At least 3 years of people management experience.
• At least 8 years of relevant work experience.
• Experience solving complex and highly ambiguous business challenges.
• Strong verbal and written communication.

PREFERRED QUALIFICATIONS

• Expertise in causal inference.
• Proficient with standard machine learning techniques.

• Some pricing optimization experience.

Amazon is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation