Applied Scientist II, Seller Fee Science

- 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. BASIC QUALIFICATIONS - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning PREFERRED QUALIFICATIONS - Experience applying theoretical models in an applied environment - Experience building machine learning models or developing algorithms for business application - Experience in designing experiments and statistical analysis of results - Experience in patents or publications at top-tier peer-reviewed conferences or journals

Amazon is a global technology company operating in e-commerce, cloud computing (AWS), digital streaming, advertising and artificial intelligence. Its India operations span development centres in Bengaluru, Hyderabad, Chennai, Pune, Gurugram and Mumbai, covering retail technology, AWS infrastructure, Alexa, advertising, payments and supply-chain systems.