GNSS Data Scientist Associate: Signals & Analysis

The University of Texas at Austin; Austin (TX); On-site; USD 89,000 - 120,000; Full time

Benefits offered by this job

Employer-paid medical coverage

Retirement contributions

Paid vacation and sick time

Paid holidays

Job summary

The University of Texas at Austin is seeking a GNSS Data Scientist Associate to design, develop, and maintain software for collection, processing, and analysis of satellite navigation signals at the Space and Geophysics Laboratory (SGL). You will independently develop data processing software using Python or C/C++, analyze navigation data with established tools, and contribute to GPS/GNSS research and testing.

Collaboration with multiple teams and thorough documentation are required.

Qualifications

• Bachelor's degree in Science, Engineering, Computer Science, or related field.
• Python or C/C++ coursework or experience.
• Data analysis coursework or experience.

Responsibilities

• Develop data processing and analysis software in Python, C/C++, or scripting to meet project objectives.
• Analyze observation and navigation data using established tools and libraries per internal practices.
• Contribute to GPS/GNSS analyses and characterizations.
• Identify improvements and new methods for GPS/GNSS data collection and analysis; develop metrics and processing techniques; assist with testing and resource planning.
• Document progress and completion of work.
• Perform other related functions as assigned.

Skills

Python

C/C++

Data analysis

Education

Bachelor's degree

Master's degree

Tools

GitLab

AWS

Job description

The University of Texas at Austin is seeking a GNSS Data Scientist Associate to design, develop, and maintain software for collection, processing, and analysis of satellite navigation signals at the Space and Geophysics Laboratory (SGL). You will independently develop data processing software using Python or C/C++, analyze navigation data with established tools, and contribute to GPS/GNSS research and testing.

Collaboration with multiple teams and thorough documentation are required.