Six Figure Work

Data Scientist, Automated Vehicle Testing

Amazon Leo

Base salary $136K  to $184K

Employer-published annual base salary, USD. Advertised base range in Redmond, WA

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  • LocationRedmond, WA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since

About this job

Amazon Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.

Export Control Requirement:

Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

We are looking for an experienced Data Scientist to help architect state-of-the-art test infrastructure and lead the development of data models and analysis tools to represent the ground truth about satellite test results in order to facilitate important business decisions. Our team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

Key job responsibilities

  • Work with engineering, software and manufacturing teams to understand drivers, impacts, and key influences on satellite performance
  • Lead the design, build and implementation of production models and make decisions in real time for satellite test results
  • Drive actions at scale to optimize test methodology and drive increases to satellite reliability
  • Analysis and modeling of satellite telemetry from test results in lab and on-orbit
  • Develop models and data pipelines for satellite telemetry
  • Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs
  • Develop scalable visualizations for analysis of satellite performance

A day in the life

As Amazon Leo Data Scientist you will own the architecture definition and development of data analysis tools to to aid engineering and production teams in deciding flight-worthiness of each Amazon Leo satellite and historical traceability tools to enable simplified discovery and interpretation of past test data. You will work with multiple engineering, software and manufacturing teams across ground and space systems, to specify requirements, define data collection, interpretation strategies, data pipelines and implement data analysis and reporting tools for Integrated Vehicle tests. Your focus will be in optimizing the analysis of test results to enable Amazon Leo production plans.

About the team

The Automated Vehicle Testing Team is a mix of scientists and software engineers responsible for data infrastructure, tools, and research that serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

Basic Qualifications

  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment

Preferred Qualifications

  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, REDMOND - 136,000.00 - 184,000.00 USD annually

Source: Amazon Leo · View original posting (opens in new tab)

Pay in context

This role's base floor ($136,000) is above 19% of the 329 Data & ML roles in Washington listed on this site; 21 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

This range next to 6 other live Amazon Leo roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Amazon Leo roles with the nearest advertised base floor
RolePublished base
Data Scientist, Automated Vehicle Testing (this listing)$136K - $184K
Sr Atlassian Admin Engineer, Amazon Leo Productivity Engineering Application Services (ALPEAS)$135,500 - $183,300
Network Development Engineer II, Satellite Systems Integration and Test, Amazon Leo$136K - $184K
Satellite Hardware Engineer, Bus Structures$136K - $184K
Hardware Dev Engineer, Amazon Leo Customer Terminal Hardware Design$136K - $184K
Data Scientist , Leo Customer Terminal$136K - $184K
Network Infrastructure Engineer, Satellite HW Test Automation, LEO Antenna Test Infrastructure$136K - $184K

Same $100K to $400K scale as every card. All Amazon Leo roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-08-20
Where this pay comes from

Location as the employer wrote it: US, WA, Redmond

USA, WA, REDMOND - 136,000.00 - 184,000.00 USD annually

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.