Senior Data Scientist, Amazon Leo

Amazon Inc.; Omaha (NE); On-site; USD 159,000 - 215,000; Full time

Job summary

Amazon Leo is seeking a Senior Data Scientist to transform satellite telemetry into actionable insights that drive system performance and reliability. You will work with large-scale time-series data from satellite payloads, ground networks, and customer terminals, developing models and automated data processing solutions to identify trends and anomalies.

The role involves collaborating with systems, hardware, software, RF, and test engineering teams to establish meaningful KPIs, correlate

Qualifications

• 5+ years of experience with SQL, Python or statistical software
• 4+ years of data science experience in engineering or analytics
• Experience with statistical models (e.g., multinomial logistic regression)
• Experience building large-scale, high-throughput data systems
• Experience in functional or operational data analysis on large datasets
• Ability to translate telemetry data into actionable recommendations

Responsibilities

• Develop scalable data processing and analytical solutions for telemetry and lab/test data
• Analyze large time-series datasets to identify performance trends and anomalies
• Correlate telemetry across subsystems to identify root causes
• Design statistical models and predictive analytics for reliability and performance
• Establish KPIs and baselines to evaluate system functionality across environments
• Develop dashboards and automated reports for engineers and leadership
• Translate findings into actionable engineering recommendations

Skills

SQL

Python

R

SAS

Matlab

Education

Master's degree in CS/Engineering/Math

Tools

AWS QuickSight

Tableau

Power BI

Redshift

Athena

S3

Job description

Senior Data Scientist, Amazon Leo

Job ID: 10594770 | Amazon Kuiper Manufacturing Enterprises LLC

Amazon Leo is seeking a Senior Data Scientist to transform complex satellite, network, and customer terminal telemetry into actionable insights that drive system performance, reliability, and engineering decisions.

In this role, you will work with large-scale datasets generated across satellite payloads, ground infrastructure, customer terminals, and end-to-end laboratory and on-orbit testing environments. You will develop analytical models, statistical methods, and automated data processing solutions to identify performance trends, detect anomalies, isolate issues, and support system validation and operational readiness.

You will partner closely with systems, hardware, software, RF, and test engineering teams to establish meaningful performance metrics, correlate telemetry across multiple system components, and translate complex technical data into clear recommendations. Your work will directly influence engineering priorities, test strategies, system improvements, and launch readiness decisions.

The ideal candidate combines strong statistical and data science expertise with practical experience analyzing complex engineering systems, processing high-volume time-series data, and developing scalable analytical solutions. Experience in satellite communications, wireless networks, or telecommunications is highly desirable.

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.

Key job responsibilities

• Develop and maintain scalable data processing and analytical solutions for satellite payload, ground network, customer terminal, and laboratory test telemetry.
• Analyze large volumes of structured and unstructured data to identify system performance trends, anomalies, degradation, and potential failure conditions.
• Correlate telemetry across satellite payloads, RF systems, networking infrastructure, customer terminals, and application-level measurements to identify relationships and isolate root causes.
• Design statistical models, machine learning techniques, and predictive analytics to detect anomalies, characterize system behavior, and identify emerging reliability or performance issues.
• Establish performance baselines, key performance indicators (KPIs), and statistical methodologies to evaluate system functionality, reliability, and performance across laboratory and on-orbit environments.
• Analyze automated test results, test campaign data, and regression trends to identify software and hardware performance changes, recurring failures, and gaps in test coverage.
• Develop dashboards, automated reports, and visualization tools that enable engineering teams and leadership to understand system health, performance, and readiness.
• Apply statistical analysis and experimental design to compare software releases, hardware configurations, and system changes, quantifying their impact on end-to-end performance.
• Translate complex telemetry and analytical findings into actionable engineering recommendations that influence test priorities, troubleshooting, product improvements, and operational decisions.
• Collaborate across multiple engineering organizations to define data requirements, improve telemetry quality, and develop consistent analytical methodologies.
• Lead the development of reusable analytical frameworks and scalable solutions that improve engineering efficiency, reduce manual investigation, and accelerate decision-making.
• Mentor engineers and data scientists in statistical methods, telemetry analysis, data interpretation, and data-driven problem-solving.

Basic Qualifications

• 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 4+ years of data scientist experience
• Experience with statistical models e.g. multinomial logistic regression
• Experience building large-scale, high-throughput, 24x7 data systems
• Experience in functional or operational data analysis, based on large volumes of data
• Experience in identifying incomplete or inaccurate data, identifying the root cause and creating/implementing an escalation plan, or experience in creating process improvements with automation and analysis
• Experience in understanding performance metrics and developing them to measure progress against key performance indicators
• Experience programmatically testing products, measuring test coverage, developing the best automation, driving testability and diagnostic
• Experience developing tools, reports, process maps, scorecards, and data visualizations that improve upon those currently employed for understanding the business and making decisions
• Experience using data, reporting, or tools to measure performance and make adjustments accordingly
• Experience solving complex problems quantitatively and develop actionable data-driven business recommendations

Preferred Qualifications

• 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines
• Experience as a leader and mentor on a data science team
• Master's degree or equivalent in computer science, engineering, mathematics or equivalent, or experience in data science, machine learning or data mining
• Experience in embedded wireless systems, or experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience troubleshooting and debugging technical systems, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience with AWS data warehouse and reporting technologies like Redshift, Athena, S3, etc.
• Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval
• Experience with data analytics platforms (Power BI, Python, SQL, Tableau), or experience in creating process improvements with automation and analysis
• Experience with one or more analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI)
• Experience in system design
• Knowledge of network design, protocols and troubleshooting
• Experience leading engineering teams as a mentor or tech lead
• Knowledge of satellite communications, RF systems, networking protocols, or end-to-end communication system performance.

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 - 159,200.00 - 215,300.00 USD annually

Preferred Qualifications

• 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines
• Experience as a leader and mentor on a data science team
• Master's degree or equivalent in computer science, engineering, mathematics or equivalent, or experience in data science, machine learning or data mining
• Experience in embedded wireless systems, or experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience troubleshooting and debugging technical systems, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience with AWS data warehouse and reporting technologies like Redshift, Athena, S3, etc.
• Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval
• Experience with data analytics platforms (Power BI, Python, SQL, Tableau), or experience in creating process improvements with automation and analysis
• Experience with one or more analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI)
• Experience in system design
• Knowledge of network design, protocols and troubleshooting
• Experience leading engineering teams as a mentor or tech lead
• Knowledge of satellite communications, RF systems, networking protocols, or end-to-end communication system performance.

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 .