DESCRIPTION

The Seller Fees team owns the end-to-end fees experience for two million active third party sellers worldwide. We own the fee technology, fee strategy, seller experience, fee integrity, fee science and data engineering to provide scalable technology to monetize all services available to third-party sellers.

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.

If big and rich data, large scale deep learning, state-of-art causal modeling and building intelligent systems excite you, we would like you to be on our team!

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.
· Collaborate with business and software teams both within and outside of the fees organization.

BASIC QUALIFICATIONS

– Experience programming in Java, C++, Python or related language
– Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
– Advanced degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
– Experience building machine learning models or developing algorithms for business application
– Experience researching about machine learning, deep learning, NLP, computer vision, data science

PREFERRED QUALIFICATIONS

– Experience implementing algorithms using both toolkits and self-developed code
– Have publications at top-tier peer-reviewed conferences or journals
– Experience with theory and practice of design of experiments and statistical analysis of results

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,400/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

USA, WA, Seattle