EO Sensor Data Analyst Engineer II - Tucson, Onsite

RTX; Albuquerque (NM); On-site; USD 69,000 - 131,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

RTX in Tucson, AZ is seeking an EO Sensor Analyst / Engineer II to develop robust data analysis tools for production Tier II Exo-atmospheric Seekers and Sensors. You will create test parameters for smooth transition from engineering to production and document algorithms and code implementations for peer reviews.

The role includes collaborating with the production test team to optimize test processes while maintaining mission assurance and addressing complex problems across multiple systems.

Qualifications

• Requires STEM degree with at least 2 years of relevant experience.
• Experience analyzing EO seeker or sensor data and using MATLAB.
• Experience with laboratory measurement equipment for optics, detectors, EO sensors.
• Experience writing technical data analysis reports.

Responsibilities

• Assess flight test performance for Tier II Exo-atmospheric Seekers and Sensors with senior engineers.
• Write flight test reports and document anomalies for program leadership.
• Develop algorithm requirements and analyze system performance; collaborate with test equipment teams.
• Lead small teams as needed and conduct test problem investigations.
• Analyze EO sensor analysis tool outputs to guide investigations of test anomalies.

Skills

MATLAB

EO data analysis

C++ programming

Test scripting

Education

STEM degree

Tools

Test equipment

Telemetry data reading

Sensor control

Job description

RTX in Tucson, AZ is seeking an EO Sensor Analyst / Engineer II to develop robust data analysis tools for production Tier II Exo-atmospheric Seekers and Sensors. You will create test parameters for smooth transition from engineering to production and document algorithms and code implementations for peer reviews.

The role includes collaborating with the production test team to optimize test processes while maintaining mission assurance and addressing complex problems across multiple systems.