Imagery Scientist (SAR) - Expert

GRVTY•St. Louis, MO

About The Position

GRVTY is seeking a motivated and experienced Imagery Scientist to serve as the subject matter expert on SAR imagery and provide technical direction across the full imagery acquisition and preparation lifecycle. The ideal candidate is an experienced SAR 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 sensors and platforms.

Requirements

Active TS/SCI Clearance with the ability to obtain a CI/Poly
4+ years as a SAR expert with understanding of collection and phenomenology, image formation processes, and exploitation products and methodologies.
Hands-on experience with SAR data processing tools and libraries including SARPy and MATLAB SAR Toolbox.
Demonstrated experience with imagery quality metrics, including RNIIRS and information theoretic-based image quality metrics, SAR-specific metrics such as Integrated Sidelobe Ratio (ISLR) and Multiplicative Noise Ratio (MNR), and sensor metadata describing geometry impacts on phenomenology (e.g., graze, squint, azimuth).
Experience exploiting SAR imagery to determine the occurrence and location of objects of interest.
Experience developing, testing, and evaluating new algorithms, processes, methodologies, and exploitation products.
Experience developing automated scientific workflows using advanced processing tools including Python, MATLAB, and Google Earth Engine.
Deep understanding of Remote Sensing Principles, Advanced imagery processing and exploitation methods, and Sensor and platform limitations and advantages.
Proven ability to communicate technical concepts to technical audiences, non-technical stakeholders, and intelligence users.

Nice To Haves

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

Responsibilities

Integrate emerging sensors and platforms into existing data pipelines and workflows.
Develop pipelines and relevant data structures for emerging capabilities.
Conduct assessment of potential differences between new sensor characteristics and capabilities compared to currently utilized platforms.
Assess potential differences in metadata, data format, and data structure characteristics in regard to changes to databases, schemas, APIs, ETL-related processes, and ingestion/movement of data within the existing data operations pipeline.
Determine how to acquire new data, including potential latency, data formats, and security domains.
Determine how to pre-process and standardize data to match existing standards or be transformed into a usable state for labeling and model development purposes, including converting between file format types and tiling full-size images into specified sizes or geospatial bounds.
Investigate gaps in emerging sensor capabilities that may require supplementation from other sources.
Explore options for coincident imagery collects from other imagery platforms to identify EO or other platforms with aligned geographic and temporal coverage and determine platforms with similar collection windows to emerging data types.
Develop and implement mathematical conversion models to transform data labels across multiple imagery types (e.g., phase history data to complex image and magnitude detected image).
Develop methods to execute tiling and pre-processing of full-size raw imagery into specified sizes and data formats while maintaining metadata and data integrity.
Generate tiles from full-size image collects with specified, precise geospatial boundaries, accounting for orthorectification to ensure geospatial accuracy at tile edges.