Interested in driving research that will shape new products that surface actionable levers to improve customer experience for Amazon’s growing 3rd party Seller population? Amazon Global Fulfillment Services is seeking an Applied Research Scientist to apply and extend state-of-the-art research in probabilistic graphs, deep bayesian networks and NLP, to help us enhance customer feedback and present opportunities to improve product listing issues and surface new customer desired features to our growing 3rd party Seller population.

You will analyze and process large amounts of text data from customers and product detail pages, evaluate state-of-the-art algorithms and frameworks, develop new algorithms to improve the Voice of the Customer product for our Sellers. You will partner with engineers and product managers to design new product features that are actionable by Sellers and improve both customer and Seller experience with Amazon.

Evaluate state-of-the-art algorithms in NLP, probabilistic graphs and deep bayesian networks
Design new algorithms that improve on the state-of-the-art to drive business impact.
Collaborate with product, UX, and tech partners to experiment new product features in production to spur Seller actions in improving customer experience
Design and plan collection of new data labels that allow us to build better models that will further improve Seller adoption and trust.
Analyze and convey results to stakeholders and contribute to the research and product roadmap




Basic Qualifications
MS in Computer Science, Machine Learning, NLP or other relevant areas
2+ years of experience in an industrial applied science setting, where your work was directly incorporated into production systems
Proficiency in Python, R, Matlab or other relevant modeling languages, and text data manipulation
Understanding of computer science fundamentals such as data structures, object-oriented design and service-oriented architectures
Ability to convey Machine Learning concepts and considerations to non-experts
Preferred Qualifications
PhD in Computer Science, Machine Learning, NLP or other relevant area
4+ years of practical work experience in building, iterating and deploying production code in end-to-end NLP solutions
Experience with combining neural networks with probabilistic/Bayesian modeling (i.e. bayesian deep learning)
Experience working with distributed processing of terabytes of text data
Significant peer reviewed scientific contributions in relevant field
Work experience in applied research and applying state-of-the-art models in an industry setting

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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About Amazon

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform.

Founded by Jeff Bezos, the Amazon.com website started in 1995 as a place to buy books because of the unique customer experience the Web could offer book lovers. Bezos believed that only the Internet could offer customers the convenience of browsing a selection of millions of book titles in a single sitting. During the first 30 days of business, Amazon fulfilled orders for customers in 50 states and 45 countries - all shipped from his Seattle-area garage.

Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improv