Applied Scientist Ii, Seller Fee Science

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Applied Science

This role focuses on applying machine learning and AI to predict and reconcile product measurements for Amazon's third-party marketplace, impacting fee strategy and seller experience. The scientist will design, develop, and deploy AI/ML models, working closely with engineering and product teams to productionize solutions and validate their business impact through rigorous experimentation.

What you'd actually do

  1. Identify opportunities to improve Seller Experience and translate ambiguous business challenges into well-defined scientific problems with measurable impact.
  2. Design, develop, and deploy AI/ML models that improve fee accuracy, automate policy-to-code translation, and enhance seller understanding of fee calculations.
  3. Partner closely with engineering and product teams to productionize solutions, meeting latency, scalability, reliability, and other system constraints.
  4. Apply rigorous experimentation, causal inference, and simulation methods to validate models and quantify business impact at scale.
  5. 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.

Skills

Required

  • building models for business application
  • 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

Nice to have

  • 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

What the JD emphasized

  • state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Other signals

  • integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy
  • improves the seller experience with AI tools
  • application of machine learning and artificial intelligence to predict and reconcile measurement of products globally
  • models, algorithms, and systems will directly influence the experience of millions of sellers
  • Design, develop, and deploy AI/ML models that improve fee accuracy, automate policy-to-code translation, and enhance seller understanding of fee calculations.