Senior Data Scientist — Regional Flexibility & AI Systems

Amazon; San Francisco (CA); On-site; USD 183,000 - 247,600; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in Sunnyvale, CA seeks a passionate Data Scientist to refine experiments and build models for regional placement automation and cross-region tooling used across Amazon. You will work with product and technical leaders to drive scalable infrastructure decisions and improve operational efficiency.

Ideal candidates have 5+ years in data science, strong SQL and Python skills, and experience with multinomial logistic regression.

Qualifications

• 5+ years experience with data querying languages (SQL) and scripting languages (Python).
• 4+ years of data scientist experience.
• Experience with multinomial logistic regression.

Responsibilities

• Enable Amazon businesses to leverage new AWS regions and improve efficiency and scale across Amazon Stores, Digital and Others businesses.
• Collaborate with product and technical leaders, advising AWS teams on SDO requirements.
• Identify enablers and blockers of region flexibility adoption, building models to assess impact of region changes and provide mitigation offerings.
• Drive the end-state architecture that enables services to break region coupling while retaining critical business functions within a region.
• Leverage data, information processing, machine learning, and generative AI to improve user experience, automation, service resilience, and operational efficiency.

Skills

SQL

Python

R

Tools

AWS QuickSight

Tableau

R Shiny

Job description

Amazon.com Services LLC in Sunnyvale, CA seeks a passionate Data Scientist to refine experiments and build models for regional placement automation and cross-region tooling used across Amazon. You will work with product and technical leaders to drive scalable infrastructure decisions and improve operational efficiency.

Ideal candidates have 5+ years in data science, strong SQL and Python skills, and experience with multinomial logistic regression.