Applied Scientist, Renewable Energy Optimization

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

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.

Amazon is looking for a passionate scientist to join the Renewable Energy Optimization (REO) team at AWS. The REO team builds software solutions and algorithms that manage and optimize Amazon's global fleet of wind and solar projects.

This is an exciting role that will provide exposure to large-scale renewable projects across the globe. We are looking for an Applied Scientist with experience building time series forecasters and a passion to apply those skills to electricity markets in a way that drives Amazon to our Sustainability goals.

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.

The ideal candidate strives in fast pace and ambiguous environments. They prefer high levels of ownership and effectively collaborate with engineering and business partners. They combine their analytical skills with a passion to accelerate with energy transition.

About the team
*Why AWS*
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

*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*
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

*Inclusive Team Culture*
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

*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.

Basic Qualifications

- 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

Preferred Qualifications

- 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.