Sr. Applied Scientist, Selling Partner Communities (SPC)

Amazon•Seattle, WA

35d

About The Position

The Selling Partner Communities (SPC) organization is dedicated to ensuring every Selling Partner (SP) achieves satisfaction with their Amazon selling experience. SPC serves as a vital bridge between sellers/vendors and Amazon, creating and managing platforms where they can connect, share knowledge, and receive help. The team's mission encompasses listening to SP feedback, advocating for experience improvements, and empowering SPs through effective, relevant, and timely communications that demonstrate Amazon's commitment to building lasting partnerships. We are seeking a Sr. Applied Scientist to join our Communities team. The successful candidate is a skilled scientist capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment.

Requirements

3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning

Nice To Haves

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.

Responsibilities

Handle challenging problems that directly impact millions of selling partners
Independently collect and analyze data
Design, develop and deliver scalable models, using any necessary programming, machine learning, and statistical analysis software
Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research
Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software
Participate in design and implementation across teams to contribute to initiatives and develop optimal solutions that benefit the SPC organization
Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.