Data Scientist II: Seller Growth & GenAI

Amazon; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Data Scientist II to advance our seller prioritization and SP growth strategy. You will work with a cross-functional team of scientists, economists, and engineers to build production-grade models that improve seller experiences and inform business decisions across the store.

You will translate business questions into scientific problems, design roadmaps for complex projects, and communicate innovations to the broader scientific community.

Qualifications

• 3+ years of data querying languages (e.g. SQL) or scripting languages (e.g. Python) experience
• 2+ years of data scientist experience
• 3+ years of machine learning/statistical modeling experience and related tooling
• Experience applying theoretical models in an applied environment

Responsibilities

• Identify opportunities to improve SP growth and translate those opportunities into science problems via principled GenAI solutions.
• 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.

Skills

SQL

Python

R/SAS/Matlab

ML modeling

Data analysis

Education

PhD in CS/Math/Stats/ML or equivalent

Job description

Amazon is seeking a Data Scientist II to advance our seller prioritization and SP growth strategy. You will work with a cross-functional team of scientists, economists, and engineers to build production-grade models that improve seller experiences and inform business decisions across the store.

You will translate business questions into scientific problems, design roadmaps for complex projects, and communicate innovations to the broader scientific community.