Amazon
Data Scientist , Music DISCO
$108K–$185K
Culver City, CA +2 · Full-time · Posted Oct 30, 2026
- Location
- Culver City, CA
Seattle, WA
San Francisco, CA - Experience
- 1+ years in data querying, scripting, or statistical/mathematical software; 2+ years in a data/research scientist, statistician, or quantitative analyst role; 1+ years creating or contributing to mathematical textbooks, research papers, or educational content.
- Education
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in STEM.
About the job
Build analytics, experiments, causal and predictive models, and measurement tools to guide Amazon Music product decisions and improve customer engagement and retention.
What you'll do
- Lead experimentation and advanced analytics, including measurement efficiency and ROI tracking.
- Build and maintain causal, structural, and predictive models for customer sentiment, engagement, and retention.
- Partner with product and engineering teams to translate business questions into science projects and data-driven product decisions.
What they ask for
- 1+ years of experience with data querying languages, scripting languages, or statistical/mathematical software.
- 2+ years of experience as a data/research scientist, statistician, or quantitative analyst at an internet-based company with complex and big data sources.
- 1+ years of experience creating or contributing to mathematical textbooks, research papers, or educational content.
- Master's degree in STEM, or experience working in STEM.
Nice to have
- Ph.D. in STEM.
- Experience working with or evaluating AI systems.
Pay
USD 122,600.00 - 160,000.00 annually base salary; USD 124,600.00 - 185,000.00 annually base salary; USD 108,300.00 - 160,000.00 annually base salary
Tools
SQL, Python, R, SAS, Matlab, SPSS, S-PLUS, Hadoop
AI focus
The role includes Gen AI initiatives and experience evaluating AI systems; preferred knowledge includes machine learning concepts and their application to reasoning and problem-solving.
Model-written summary · the original posting is authoritative