Amazon
Data Scientist, Automated Vehicle Testing
$136K–$184K
REDMOND, WA +1 · Full-time · Posted Aug 20, 2026
- Location
- REDMOND, WA
Redmond, WA - Experience
- 2+ years of data scientist experience; 3+ years of experience with data querying/scripting languages or statistical/mathematical software; 3+ years of machine learning/statistical modeling and data analysis experience; 1+ years working with or evaluating AI systems.
- Education
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in STEM.
- Visa sponsorship
- Candidates must be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
About the job
Architects data infrastructure, models, and analysis tools for automated satellite testing to support flight-readiness decisions and improve manufacturing and satellite reliability.
What you'll do
- Partner with engineering, software, and manufacturing teams to analyze satellite performance and define test data strategies.
- Build production models, telemetry pipelines, and analysis tools for satellite test results.
- Create and manage datasets for LLM continued pre-training and supervised fine-tuning, and optimize testing methods.
What they ask for
- 3+ years of experience with data querying or scripting languages, or statistical/mathematical software.
- 3+ years of experience with machine learning or statistical modeling, data analysis tools and techniques, and performance parameters.
- 1+ years of experience working with or evaluating AI systems.
- Master's degree in STEM, or experience working in STEM; experience applying theoretical models in an applied environment.
Nice to have
- Experience defining and creating benchmarks for GenAI model performance.
- Knowledge of machine learning concepts and their application to reasoning and problem-solving.
Pay
136,000.00 - 184,000.00 USD annually (base salary)
Tools
SQL, Python, R, SAS, Matlab, Perl
AI focus
Work with or evaluate AI systems; create and manage datasets for continued pre-training and supervised fine-tuning of LLMs; potentially define benchmarks for GenAI model performance.
Model-written summary · the original posting is authoritative