This is a strategic role to form and deliver our technical technique in developing and deploying NLU, Machine Learning solutions to our hardest buyer dealing with issues. Our goal is to delight customers by offering a conversational interplay. These initiatives are on the heart of the organization and recognized as the improvements that will permit us to construct a differentiated product that exceeds customer expectations.
We’re a high vitality, quick growth enterprise excited to have the opportunity to shape Alexa Shopping NLU is outlined for years to return. If this role looks like an excellent fit, please reach out, we might love to talk to you.This position requires working closely with enterprise, engineering and other scientists within Alexa Shopping and throughout Amazon to ship ground breaking options.
At Alexa Shopping, we attempt to enable purchasing in on a regular basis life. We enable customers to immediately order no matter they want, by merely interacting with their Smart Devices similar to Amazon Show, Spot, Echo, Dot or Tap. Our Services let you shop, no matter the place you’re or what you might be doing, you’ll be able to go from ‘I want that’ to ‘that is on the way in which’ in a matter of seconds. We are seeking the trade’s greatest to assist us create new methods to work together, search and shop. Join us, and you’ll be taking part in changing the future of everyday lifeWe are looking for a Data Scientist to be a part of the NLU science staff for Alexa Shopping.
They will work nicely in a team setting with people from various disciplines and backgrounds. They will function an ambassador for science and a scientific resource for enterprise groups, in order that scientific processes permeate all through the HR organization to the good thing about Amazonians and Amazon. Ideal candidates will own the development of scientific models and manage the data evaluation, modeling, and experimentation that’s needed for estimating and validating mannequin model.
They will work intently with engineering groups to develop scalable information assets to help speedy insights, and take profitable models and findings into production as new products and services. They might be customer-centric – clearly speaking scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering profitable scientific options.