Business Intelligence Engineer, Fee Strategy

As a Business Intelligence Engineer I in the Fee Strategy organization, you'll be at the forefront of shaping how Amazon monetizes its 3P business globally, leveraging data as your superpower to drive fee frameworks that impact millions of Selling Partners on our platform!
Dive into the world of marketplace economics where your analytical expertise will help establish fee structures, programs, and magnitudes that power Amazon's global 3P business. You'll uncover hidden patterns in seller behavior, estimate and measure the impact of fee changes, and drive strategic innovations that directly impact over 2MM+ active sellers worldwide. This work feeds into a long-term vision of building a closed-loop fee setting process that minimizes human judgment and maximizes data-driven decision-making. In this high-impact role, you'll collaborate with economists, scientists, SDEs, product managers, and business leaders to tackle fascinating challenges at the intersection of pricing strategy, financial modeling, and global commerce.
The Fee Strategy organization is where data meets real-world impact, every framework you build and every insight you generate directly influences fee programs across global stores, shaping seller economics, marketplace competitiveness, and Amazon's bottom line. If you're passionate about leveraging the latest analytical techniques (including GenAI) to solve complex strategic puzzles around fee optimization at massive scale and significance, this role offers the perfect blend of intellectual rigor, scientific depth, and meaningful business impact!
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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