Applied Scientist, Demand Forecasting

Benefits

Parental leave

20 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Offered From the posting source checked Jun 20, 2026

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

$172K-$223K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

77% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Applied Scientist, Demand Forecasting Bellevue, Washington, USA 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 what's 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. You'll 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. You'll 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, you'll 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

Read the full description at www.amazon.jobs. FewerJobs shows a preview and links to the original posting.