Senior Applied Scientist, Amazon Stores Economics & Science (SEAS)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• 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

$192K-$260K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

Role benchmark (BLS OEWS)

$111,944 typical for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

102% 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.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Applied Scientist, Amazon Stores Economics & Science (SEAS) Seattle, Washington, USA Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. We are team of passionate Applied Scientists, Research Scientists, and Economists collaborating to uncover, formulate, and solve big bet issues for broader Stores organization, including marketplace efficiency, seller incentive design, and inventory optimization. We are seeking to add another member to our team who thrives in inter-disciplinary, ambiguous, and high visibility environments. Key job responsibilities The successful candidate will lead large-scale science initiatives from research to production and translate complex business problems into mathematical frameworks. They will design and implement large-scale optimization algorithms for complex supply chain and marketplace problems, and design incentive-compatible mechanisms for marketplace challenges including auction design, matching algorithms, and pricing strategies. The ideal candidate will have a strong publication record in top-tier conferences/journals (INFORMS, EC, WINE, ICML, NeurIPS, etc.) and experience coordinating cross-functional projects. They should have hands-on experience building science

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