We are a team of scientists and engineers supporting AWS product leaders to make high-impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We come from diverse backgrounds in statistics, computer science, engineering, and business analytics. We specialize in the full end-to-end ML development process, including data ingestion, ETL, model development, and model deployment in production.
We support data science needs across AWS EC2, Database & Analytics, and S3 teams using deep learning, graph neural networks, forecasting, reinforcement learning, causal inference, and more.
High Impact Projects: We work on high-impact, high-visibility projects that directly influence AWS product roadmaps and senior leaders' decisions.
Supportive Team Environment: We are proud of our supportive and inclusive team culture, we have each other's back during ups and downs.
Work-Life Balance: We believe 80% of value comes from 20% of work, so we always prioritize our backlog ruthlessly based on business value.
Learning Opportunity: Extensive opportunities to understand AWS business and leverage state-of-the-art AI/ML and cloud technology.
- Bachelor's degree in engineering, statistics, computer science, mathematics, or a related quantitative field
- 10+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- Competency in data querying languages (e.g., SQL) and scripting languages (e.g., Python, R)
- Experience with advanced machine learning techniques including deep learning, causal inference, and experimentation systems
- Experience leading large-scale technical or scientific programs with a proven record of thought leadership and successful delivery
- Track record of influencing senior leadership (Director/VP level) through data-driven insights and strategic recommendations
- PhD or Master's degree in Computer Science, Statistics, Machine Learning, Economics, Operations Research, or a related quantitative field
- Knowledge of AWS technology stack or Certification
- Experience with Gen AI, large language models, Baysian, Econometrics, or reinforcement learning in applied settings
- Demonstrated ability to build and mentor high-performing science teams
- Experience establishing measurement frameworks and experimentation systems at scale
- Excellent communication skills with non-technical executive audiences
- Publication experience at top-tier conferences or journals
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.
Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle – 189,400.00 - 256,200.00 USD annually
