Data Scientist, Seller Fee Science

ADCI - BLR 14 SEZ•3h ago

IN, KA, BengaluruOnsiteFull-timeMid Level2+ yrs exp

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Data ScientistVp Data

The Seller Fee Science Team integrates economic modeling, machine learning
artificial intelligence to guide fee strategy, quantify its impact
ensure fees are accurately computed and explained for billions of transactions between Amazon selling partners and customers. We help build the foundations for growing selling partner businesses, bringing the best selection and prices to Amazon customers
helping Amazon leaders make and implement high impact decisions that optimally balance profitability and growth. Our team brings together world-class economists, physicists, mathematicians
computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. As an data scientist on our team, this role will focus on the application of data analysis, econometrics, machine learning
artificial intelligence to measure and predict Amazon's P&L, with emphasis on fee revenue. This blends the tools of data science, statistics
ML/AI. Your work will shape not only how fees are decided, but how they are interpreted and planned. We are seeking scientists who are motivated by first principles, disciplined experimentation
the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where analytic rigor meets real-world complexity
where your analysis, models, algorithms
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 ** Translate ambiguous business challenges into well-defined scientific problems with measurable impact. ** Identify opportunities to improve fee revenue measurement, prediction, planning, structure
level. ** Identify opportunities to improve measurement
prediction of other items of the P&L, at appropriate levels of granularity. ** Design, develop
deploy econometric or AI/ML models that improve our understanding of the relationship between fees and costs
other elements of the P&L. ** Partner closely with finance and fee strategy teams to formulate scientific questions, communicate results
productionalize solutions. **Apply rigorous 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
technical artifacts. About the team Amazon’s third-party marketplace is a multibillion-dollar global service, connecting customers and sellers across through billions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning
artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products
improve the seller experience with AI tools that support any fee related contact (understanding, audit
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
computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact.
2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques
parameters that affect their performance experience - 1+ years of guiding and coaching a group of researchers experience - 1+ years of working with or evaluating AI systems experience - 1+ years of creating or contributing to mathematical textbooks, research papers
educational content experience - Master's degree in Science, Technology, Engineering
experience working in Science, Technology, Engineering
Mathematics (STEM) - Experience applying theoretical models in an applied environment
Ph.D. in Science, Technology, Engineering
Mathematics (STEM) - Knowledge of machine learning concepts and their application to reasoning and problem-solving - Experience in Python, Perl
another scripting language - Experience in a ML or data scientist role with a large technology company - Experience in defining and creating benchmarks for assessing GenAI model performance - Experience working on multi-team, cross-disciplinary projects - Experience applying quantitative analysis to solve business problems and making data-driven business decisions - Experience effectively communicating complex concepts through written and verbal communication Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Required skills

PythonSQLRSASMatlabmachine learningdata analysis