Amazon Sr Applied Scientist Renewable Energy Optimization 

United States, Washington, Seattle 

10864637

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.As an Applied Scientist on the REO team, you will support all lifecycles of our ML based optimization solutions. This includes maintaining day-to-day reliability, scaling/refining the current solutions and experimenting with new optimization opportunities that support AWS's Energy and Sustainability ambitions.About the team
*Why AWS*
*Diverse Experiences*
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.*Work/Life Balance*
*Inclusive Team Culture*
*Mentorship and Career Growth*
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- Master's degree in math/statistics/engineering or other equivalent quantitative discipline
- Experience programming in Java, C++, Python or related language
- 5+ years translating business problems into machine learning solutions and algorithms
- Passion for the power industry and/or electricity markets

- PhD in math/statistics/engineering or other equivalent quantitative discipline
- 3+ years building with Jupyter Notebook
- Experience in deploying and optimizing ML solutions in a production environment.
- Experience with modeling tools such as Pytorch and Jax
- Deep Experience with Mathematical Optimization or Time Series Forecasting.
- Experience in electricity markets