Business Intel Engineer II, SCOT - Automated Inventory Management
Amazon - Bellevue, Washington, USA
Posted May 15, 2026
Benefits
- Parental leave
- Not verified not verified - source not recorded; timestamp not recorded
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- 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
16% 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
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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
Business Intel Engineer II, SCOT - Automated Inventory Management Bellevue, Washington, USA The Supply Chain Optimization Technologies (SCOT) organization owns Amazon's global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are automated large-scale business operations, inventory and supply chain planning and optimization systems. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon's inventory investment and placement decisions. The Automated Inventory Management team within SCOT seeks an experienced and motivated Business Intelligence Engineer to develop analytical models and tools to automate the auditing of the SCOT systems. Such tools may include algorithms, metric bridges, dashboards, processes and workflow systems. The successful candidate will have strong quantitative data mining and modeling skills and be comfortable working on new and sometimes ambiguous problems from concept through to execution. They will have strong communication and leadership skills, will be able to collaborate with other teams (e.g. software development, business owners, product managers) and to present findings to senior audiences to drive business improvements. As well we expect this candidate to raise the bar on any of the following categories: Data Warehousing, Data Architecture, Performant Self Service Toolsets and Data analytics. Candidate might be willing to work with the others BIEs in order
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