Applied Scientist, SCOT-Inbound Systems
Amazon - Bellevue, Washington, USA
Posted May 20, 2026
Benefits
- Parental leave
- Not verified not verified - source not recorded; timestamp not recorded
- Non-birth-parent leave
- Not verified not verified - source not recorded; timestamp not recorded
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
50% above the BLS national median 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.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Applied Scientist, SCOT-Inbound Systems Bellevue, Washington, USA As part of IRR (Inventory Routing and Replenishment) organization within SCOT-Inbound systems, Applied Scientists own algorithms powering inventory routing, replenishment, and modeling / simulation of Amazon's fulfillment network utilizing optimization and machine learning toolsets. We are looking for a talented applied scientist with a passion for designing and implementing efficient and elegant scientific solutions for Amazon-scale supply chain problems. Key job responsibilities - Design and develop advanced mathematical optimization and machine learning solutions in the domains of inventory optimization, distribution optimization, network design, and control theory. - Use methods in learned and model-based online and offline control techniques and algorithms to design efficient exact or heuristic solution methodologies to be used by in-house decision support tools and software. - Research, prototype, simulate, and experiment with these models using programming languages such as Java and Python; participate in the production level deployment. - Closely work with software engineering teams and write well-tested production Java/Python code for science modules within engineering-managed services. Provide time-sensitive on-call support and high-severity issue support when bugs are identified in production code. Improve code quality of legacy scientific production code. - Create, enhance, and maintain technical documentation and science designs. - Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders. - Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans. - Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists. A
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