Senior Applied Scientist, AWS Central Economics and Science
About the role
AWS is looking for an entrepreneurial, analytical, creative, and flexible leader to help redefine the information technology industry. The ACES Sales Channels team is hiring an Applied Scientist (Senior or below) to advance the mission of providing rigorous, causal-inference-driven recommendations for AWS sales optimization.
Responsibilities
- Causal ML System Development: Build and deploy machine learning models that emphasize causal inference, ensuring recommendations are grounded in valid interventions
- Incentive Design: Define and model incentives that drive desirable behaviors across AWS sales channels, partner programs, and reseller ecosystems
- Stakeholder Collaboration: Work with business stakeholders to understand requirements, validate approaches, and ensure practical applicability of scientific solutions
- Scientific Rigor: Promote findings at internal conferences and contribute to the team's reputation for methodological excellence
Requirements
- 3+ years of building machine learning models for business applications
- PhD or Master's degree
- Experience programming in Java, C++, Python, or related language
- Experience with neural deep learning methods and machine learning
Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Benefits
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.
Pay
USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually USA, NY, New York - 183,800.00 - 248,700.00 USD annually USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
Schedule
We offer a hybrid work model, allowing employees to choose between working in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.