Amazon Applied Scientist Seller Fees Science & Tech 

United States, Washington, Seattle 

12019958

We are looking for an Applied Scientist to join us on improving accuracy in billion-scale fee transactions worldwide and enhancing selling experience with fee policies and services. In this role you will develop large scale machine learning models to drive the fee calculations that impact hundreds of millions of products from third-party sellers in the Amazon product catalog. You will leverage sophisticated statistical methods, supervised and unsupervised learning models, as well as generative AI that can scale to production requirements worldwide. You will participate in developing models at the intersection of deep learning and causal inference. You will collaborate with other Applied Scientists, Research Scientists, Data Scientists, Economists, Software Developers, and Product Managers.Key job responsibilities
Responsibilities:
. Design measurable and scalable science solutions that can be adapted across stores worldwide with different languages, policy and requirements.
· Develop large scale classification and prediction models using the rich features of text, image and customer interactions and state-of-the-art techniques.
· Research and implement novel machine learning, statistical and econometrics approaches.
· Write high quality code and implement scalable models within the production systems.
· Stay up to date with relevant scientific publications.

- 3+ years of building models for business application experience
- PhD, or Master's degree and 3+ years of building machine learning models or developing algorithms for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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 building machine learning models or developing algorithms for business application

- Experience using Unix/Linux
- Experience in professional software development
- Experience implementing algorithms using both toolkits and self-developed code
- Experience in designing experiments and statistical analysis of results