Applied Scientist Manager Amazon
Seattle, WA

Job Description

Are you passionate about building systems that process massive amounts of data? Are you excited by developing and productionizing machine learning, deep learning and computer vision algorithms? Do you enjoy working with a huge diversity of engineers, machine learning scientists, and user-experience designers? If so, you have found the right match!

The vision for Amazon Fashion is to create services, processes, tools and platforms to support innovative and engaging fashion experiences. The Fashion Science team at Amazon aims to make Amazon the number one online shopping destination for Fashion. We are seeking an Applied Scientist Manager who has a solid background in applied Machine Learning and Computer Vision, deep passion for building data-driven products and has a proven track record of leading scientists to execute complex projects and deliver solutions that directly impact millions of Amazon customers.

Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique challenges in areas such as product recommendations, product discovery and data quality. The Fashion Science team builds large-scale machine learning systems to address these. We leverage the massive computing power of Amazon Web Services as well as big data technologies such as Spark and Hadoop to build data pipelines for hundreds of millions of products. Our data is used by numerous front-end teams to deliver amazing experiences to customers all around the world.

Major Responsibilities:

* Lead a group of research and applied scientists that design and build machine-learning, natural language processing, and computer vision solutions for our customers
* Develop science and engineering roadmaps, and foster cross-team collaboration to execute complex projects.
* Collaborate with PMs in Designers on customer-facing experiences that will utilize this data to transform the apparel shopping experience for Amazon customers.
* Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
* Drive continued scientific innovation as a thought leader and practitioner.
* Hire and develop top talent, provide technical and career development guidance to both scientists and engineers in the organization.