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 principles, disciplined experimentation, and the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where mathematical rigor meets real-world complexity, and where your models, algorithms, and systems will directly influence the experience of millions of sellers. If you are driven to build elegant solutions to hard problems—and to see them operate in production at meaningful scale—we would welcome the opportunity to build with you. Key job responsibilities - Identify opportunities to improve Seller Experience and translate ambiguous business challenges into well-defined scientific problems with measurable impact. - Design, develop, and deploy AI/ML models that improve fee accuracy, automate policy-to-code translation, and enhance seller understanding of fee calculations. - Partner closely with engineering and product teams to productionize solutions, meeting latency, scalability, reliability, and other system constraints. - Apply rigorous experimentation, causal inference, and simulation methods to validate models and quantify business impact at scale. - Communicate scientific innovations and results clearly to cross-functional stakeholders and contribute to the broader internal and external scientific community through publications, talks, and technical artifacts.
