Imagery Scientist SAR- Expert

Imagery Scientist (SAR)- Expert

St. Louis, MO

TS/SCI

Apply for this job

What Impact You'll Have

GRVTY is seeking a motivated and experienced imagery scientist to serve as the lead SAR subject matter expert (SME) on our dynamic team. The ideal candidate is an expert imagery scientist with a passion for advanced scientific problem solving, imagery exploitation, and operational intelligence support. This role will drive solutions informed by specific phenomenology limitations and advantages of the sensors and platforms in mind.

What You'll be Owning

• Serve as the lead technical authority for SAR exploitation and imagery science initiatives.

• Analyze:

• SAR collection characteristics

• Sensor phenomenology

• Image formation processes

• Develop, test, and evaluate:

• New algorithms

• Exploitation methodologies

• Scientific workflows

• Automated processing techniques

• Utilize advanced processing tools including:

• Python

• MATLAB

• Google Earth Engine

• SARPy

• Conduct exploitation and analysis of SAR imagery to identify and locate objects of interest

What You Must Have

• Active TS/SCI Clearance with the ability to obtain a CI/Poly

• 6+ years of advanced SAR exploitation and imagery science experience

• Demonstrated expertise in:

• SAR collection and phenomenology

• Image formation processes

• Exploitation methodologies

• Sensor metadata interpretation

• Hands-on experience with:

• SARPy

• MATLAB SAR Toolbox

• Strong knowledge of:

• RNIIRS

• Information theoretic image quality metrics

• Integrated Sidelobe Ratio (ISLR)

• Multiplicative Noise Ratio (MNR) h)

• SAR geometry impacts

• Experience developing and evaluating:

• Algorithms

• Automated workflows

• Scientific exploitation methods

• Strong skills using:

• Python

• MATLAB

• Google Earth Engine

• Deep understanding of:

• Remote sensing principles

• Advanced imagery exploitation

• Geospatial intelligence methodologies

• Proven ability to communicate technical concepts to:

• Technical audiences

• Non-technical stakeholders

• Intelligence users

What Would be Nice to Have

• Experience applying CV and machine learning (ML) techniques to SAR imagery and data to address intelligence problems