Data Scientist - Phased-Array Satellite Validation

Amazon Kuiper Manufacturing Enterprises LLC; Redmond (WA); On-site; USD 150,000 - 210,000; Full time

Job summary

Amazon Kuiper Manufacturing Enterprises LLC is seeking a Data Scientist to turn satellite telemetry into actionable engineering decisions. You will connect data from manufacturing, ground tests, and in-orbit operations to trace behavior, detect anomalies, and drive design improvements across the fleet.

The role emphasizes building baselines, early warning indicators, and reliability estimates, with collaboration across hardware, firmware, and reliability teams to ensure solutions are practical

Qualifications

• Master’s degree or above in a quantitative field such as statistics, mathematics, data science, physics, electrical or aerospace engineering, or computer science, or PhD.
• 3+ years hands-on experience in applied/industrial data analysis using Python and SQL on large time-series/telemetry data.
• Experience applying statistical methods to noisy, real-world data.
• Experience building visualizations and dashboards to communicate findings to engineers and decision makers.

Responsibilities

• Connect telemetry data with production/test data to inform engineering decisions.
• Form hypotheses about hardware behavior and defend them to hardware, firmware, and reliability engineers.
• Design ground tests and determine what to test and how many runs are needed.
• Build fleet-level baselines and early-warning indicators to catch issues before outages.

Skills

Python

SQL

Time-series analysis

Anomaly detection

Statistical methods

Data visualization

Problem framing

Collaboration with hardware/software

Education

Master’s degree or PhD in a quantitative field

Tools

Spark

Athena/Presto

Redshift

AWS

Job description

Amazon Kuiper Manufacturing Enterprises LLC is seeking a Data Scientist to turn satellite telemetry into actionable engineering decisions. You will connect data from manufacturing, ground tests, and in-orbit operations to trace behavior, detect anomalies, and drive design improvements across the fleet.

The role emphasizes building baselines, early warning indicators, and reliability estimates, with collaboration across hardware, firmware, and reliability teams to ensure solutions are practical