Applied Scientist, Demand Forecasting

What does it take to build a foundation model that can forecast demand for hundreds of millions of products including ones that have never been sold before

At Amazon our Demand Forecasting team is tackling one of the most ambitious challenges in applied time series research: designing and building large-scale foundation models that generalize across an enormous and diverse catalog of products geographies and business contexts. This is not incremental modeling work. We are redefining whats possible in demand forecasting through novel architectures training strategies and data generation techniques.

Our team operates at a scale that is unmatched in industry or academia. Youll design experiments across millions of products simultaneously developing new model architectures and training methodologies that push the boundaries of what foundation models can learn from vast heterogeneous time series data. Youll explore techniques in transfer learning zero-shot forecasting and synthetic data generation.

The models you design here will ship to production and directly influence hundreds of millions of dollars in automated inventory decisions every week. Beyond operational impact youll publish your work at top-tier conferences and contribute to advancing the state of the art in time series foundation models for the broader scientific community.

If you are a scientist who wants to work at the frontier of time series research design novel solutions to problems no one else has solved at this scale and see your research deployed to real-world impact this is the team for you.

Key job responsibilities
1. Design and implement novel deep learning architectures (e.g. Transformers SSMs or Graph Neural Networks) for time-series foundation models that generalize across hundreds of millions of products and diverse global contexts.

2. Drive the full development cycle - from whiteboarding new algorithmic approaches to overseeing production-scale deployments.

3. Collaborate with SDEs to build high-performance distributed training and inference pipelines; translate complex scientific concepts into scalable production-grade code in Python and Scala.

4. Leverage and develop agentic GenAI workflows to automate the end-to-end research cycle from synthesizing state-of-the-art literature and auto-generating experimental code to rapidly iterating on model architectures across millions of products.

5. Maintain a high bar for scientific excellence by publishing novel research in top-tier venues (e.g. NeurIPS ICLR KDD) and contributing to Amazons internal patent and science community.

A day in the life
No two days look the same but most will involve a high-velocity blend of deep architectural work distributed system design and frontier scientific thinking at a scale you wont find anywhere else.

You might start the morning by designing a synthetic data pipeline to stress-test your foundation model. Youll use generative techniques to simulate rare black swan supply chain events ensuring your model remains robust where historical data is thin. Youll then lead a Scientific Design Review walking senior leaders through your models architecture defending your choice of loss functions with data-driven rigor.

Youll write high-performance code often paired with AI-coding assistants to handle the heavy lifting of boilerplate and unit testing. Youll collaborate across a Two-Pizza Team of scientists and engineers pushing the boundaries of research with a clear goal: contributing to work that will be published at top-tier venues (ICLR NeurIPS) while simultaneously driving multi-million dollar automated decisions.

The work is hard the math is complex and the tools are state-of-the-art. If you want to build the models that actually shipthis is where you do it.

About the team
The Demand Forecasting team sits at the heart of Amazons supply chain building the science that determines what products are available when and at what cost for hundreds of millions of customers around the world. Our mission is to push the frontier of whats possible in large-scale time series forecasting and to deploy that science where it creates real measurable impact.

We are a team of scientists who care deeply about both research rigor and real-world outcomes. We dont just publish we ship. And we dont just ship we measure iterate and raise the bar. Our work spans the full lifecycle: from foundational research and large-scale experimentation to production deployment and downstream impact measurement across supply chain inventory and financial planning.

- PhD or Masters degree and 3 years of deep learning computer vision human robotic interaction algorithms implementation experience
- 3 years of building models for business application experience
- Experience programming in Java C Python or related language

- PhD in computer science machine learning engineering or related fields
- Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers
- Experience operating highly available distributed systems of data extraction ingestion and processing of large data sets or experience with training and deploying machine learning systems to solve large-scale optimizations
- Strong publication record in top-tier AI/ML conferences (e.g. NeurIPS ICLR ICML KDD CVPR) or a history of contributing novel algorithmic improvements to production-scale systems.
- Fluency in Python.

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 for more information. If the country/region youre applying in isnt 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 WA Bellevue - 142800.00 - 193200.00 USD annually