Applied Scientist II, Seller Fee Science

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

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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

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

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About this role

Applied Scientist II, Seller Fee Science Bengaluru, Karnataka, IND Amazon's third-party marketplace is a multibillion-dollar global ecosystem, connecting customers and sellers across the world through millions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improves the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. For example, precision measurement of difficult to measure products, large-scale simulation of sales, inventory, and policy changes, as well as leveraging natural language understanding and automated reasoning to interpret policy, generate code, resolve disputes, audit fees, and respond to sellers at meaninful scale. As an applied scientist on our team, this role will focus on the application of machine learning and artificial intelligence to predict and reconcile measurement of products globally. This blends together statistical modeling, application of NLP, image processing, classical machine learning, cost-benefit analysis, causal modeling, and optimization. Your work will shape not only how fees are implemented, but how they are interpreted, experienced, and trusted at scale. You will partner closely with engineers and product partners to take your solutions from research to production. We are seeking scientists who are motivated by first

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