Data Scientist II: SP Growth & GenAI Strategy

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.com LLC in Seattle, WA seeks a Data Scientist II to advance seller prioritization, analytics, and growth strategies for Selling Partner customers. You will collaborate with engineering, research, and business teams to deliver impactful, seller-centric insights and scalable models for production use.

The role requires deep business domain understanding, hands-on ML expertise, and demonstrated ability to communicate complex results to diverse audiences.

Qualifications

• 3+ years of data querying languages (e.g. SQL) or scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab) experience.
• 2+ years of data scientist experience.
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
• 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

Matlab

SAS

ML modeling

Education

PhD in computer science/math/statistics/ML

Tools

GenAI tools

ML frameworks

Job description

Amazon.com LLC in Seattle, WA seeks a Data Scientist II to advance seller prioritization, analytics, and growth strategies for Selling Partner customers. You will collaborate with engineering, research, and business teams to deliver impactful, seller-centric insights and scalable models for production use.

The role requires deep business domain understanding, hands-on ML expertise, and demonstrated ability to communicate complex results to diverse audiences.