Economist, Seller Fees Science
4 settimane fa
Job ID: 2723491 | Amazon.com Services LLC
We are seeking an Economist to help evaluate and advance the science of determining third-party seller fees and incentives. The working environment is collaborative and interdisciplinary. The successful candidate will:
Leverage economic methods like modeling and impact estimation to address key issues using large, real-world datasets;Partner with PMs and BAs to identify data and define metrics evaluating business initiatives and making recommendations;Execute from idea to implementation as an integral part of cross-functional teams;Thrive in a highly complex and fast-paced environment.Key job responsibilities: Build causal inference modeling to evaluate the effects of policy changes, such as fee adjustments and new fee structures, on seller behaviors and business metrics;Analyze how sellers and key outcomes are impacted by variations in growth strategies;Design experiments to measure pilot programs and support scaling-up efforts;Synthesize learnings from past policy changes into critical insight to help the business develop new strategies and make science-based decisions.About the team: The Seller Fees team owns the end-to-end fees experience for third-party sellers WW. We develop monetization strategies, economics and science models, and software that accurately charge sellers fees while optimizing long-term Amazon growth, allowing sellers to offer customers outstanding selection at sharp prices. Our systems let Amazon teams launch and change fees in ways that build seller trust, ensuring every transaction is accurately calculated and transparent.
The fee domain includes Fee Strategy, Seller Experience, Seller Economics, ML, Data Science and Analytics, payments accuracy and integrity, and provides scalable technology to monetize Amazon's services available to third-party sellers.
BASIC QUALIFICATIONS- PhD in economics or equivalent
PREFERRED QUALIFICATIONS- 2+ years of industry, consulting, government, or academic research experience
- Knowledge of at least one statistical software package such as R, Stata, Matlab, SAS
- Experience in prediction and forecasting in a research or industrial environment
- Experience with handling large datasets
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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