Applied Scientist, Seller Growth Science

Amazon•Seattle, WA

About The Position

Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for an Applied Scientist II to work on our growth agent vision on seller recommendation to improve our SP growth strategy and drive new seller success. As a successful applied scientist on our talented team of applied scientists and economists, you will translate complex business problems into science solutions using a variety of machine learning techniques, and collaborate with engineering, research, and business teams to deliver impactful experiences on behalf of our sellers. You need to have deep understanding of the business domain and have the ability to bridge business needs with scientific approaches. You are also strong in machine learning methodology and scientific foundation with the ability to collaborate with engineering to put models in production to answer specific business questions. You excel at identifying the right ML techniques—whether supervised learning, causal inference, optimization, or other approaches—to solve diverse business challenges. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).

Requirements

PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience in solving business problems through machine learning, data mining and statistical algorithms

Nice To Haves

Experience using Unix/Linux
Experience in professional software development
Experience in designing experiments and statistical analysis of results
Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
Experience identifying opportunities to integrate AI solutions into products and services to drive business value.

Responsibilities

Identify opportunities to improve SP growth and translate those opportunities into science problems.
Design and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.
Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
Be responsible for communicating our science innovations to the broader internal & external scientific community.