AWS Central Economics and Science is looking for an applied optimization scientist to join the Capacity Economics team. This scientist will work at the intersection of economics and optimization, contributing to projects that span both the Capacity Economics team and the EC2 Optimization Science team within the EC2 Capacity Org.

The Capacity Economics team is a small, applied-solutions-focused group of economists and scientists focused on lowering AWS' cost-to-serve through science-based models, analyses, and insights. Our work spans pricing design, capacity allocation, and infrastructure economics—problems that require both rigorous quantitative methods and a deep understanding of how markets and incentives shape outcomes. The candidate will work on a portfolio of projects that include optimizing internal prices for compute resources and working across Finance, Engineering, and Capacity stakeholders to design mechanisms that align incentives and reduce costs. The role will also engage with the infrastructure organization, including Amazon Cloud Logistics, to support the efficient transit and deployment of server rack builds.

Key job responsibilities
On the EC2 Optimization Science (EC2-Opt Sci) side, the candidate will contribute to the design, implementation, and scaling of decision-making algorithms that manage EC2's virtual and physical capacity systems. EC2 Capacity owns EC2's top-level customer satisfaction metric—capacity availability—and the forecasting and decision-making systems that drive significant Cap Ex investments in server ordering for AWS data centers. Optimization Science is a core team involved in the end-to-end design and implementation of decision-making systems that manage the trade-off between Cap Ex and capacity availability while matching demand and supply at different planning horizons. The candidate will participate in science and engineering reviews with the Optimization Science team and will be expected to contribute to the rigor and quality of that team's technical work.

In a typical optimization science project, we analyze large volumes of data and develop prescriptive optimization models with inputs from ML or statistical models and business users. Solution approaches are validated through simulations and/or production A/B tests. Success requires scientific breadth to understand the interactions between different phases of a project—from data analysis through to production—including resolving issues after rollout.

As an Applied Scientist working on an optimization project, you will be hands-on with mathematical modeling and implementation and will contribute to the design of engineering systems with scalability, extensibility, maintainability, and correctness in mind. You will review approaches by other scientists and engineers in terms of business relevance, technical validity, engineering/science interface, and computational performance. Communicating results to guide business direction and working with software development teams to implement ideas in code is key to success. You will write technical and business documents that influence engineering investments and business direction. Collaborating with scientists, software engineers, economists, and product managers, you will develop creative, novel, and data-driven approaches to improve cloud compute offerings and impact the bottom line of AWS.

A day in the life
The mission of the ACES Capacity Economics Team is to provide AWS Finance and AWS Service teams with economic frameworks, statistical models, and system-design insights to understand and optimize AWS’ cost structure. Internally, we succinctly boil our objective down to this: to help AWS to serve its total demand at a lower cost.

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.

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 Amaze Con conferences, inspire us to never stop embracing our uniqueness.

Mentorship & 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.

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.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development

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.

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 - 142,800.00 - 193,200.00 USD annually