> Markdown version of [/jobs/ext/736851-imagery-scientist-eo](https://www.wearedevelopers.com/jobs/ext/736851-imagery-scientist-eo). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Imagery Scientist (EO) - **Company:** Geo Owl - **Location:** Springfield, VA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computer Vision, Cloud Computing, Data Integrity, Extract Transform Load (ETL), Google Earth, Image Quality, Information Theory, Python (Programming Language), MATLAB, Machine Learning, Apache Maven, Metadata, Data Pipelines - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9c7514da128f6357 ## About the Role Do you have experience in Satellite data analysis?, Do you have a Master's degree?, * *Active TS/SCI clearance * *Minimum 18 experience points required (see experience point calculation below) * *4+ years as an EO expert with deep understanding of collection, phenomenology, image formation process, and exploitation products * *Experience exploiting the electromagnetic spectrum (electro-optical) to determine the occurrence and location of objects of interest * *Experience developing, testing, and evaluating algorithms and processes using EO imagery; proficiency with Python, MATLAB, Google Earth Engine, or similar advanced processing tools * *Experience communicating EO capabilities, methodologies, and products to both technical and non-technical audiences * *Deep understanding of remote sensing principles, imagery processing, and advanced exploitation methods; experience with NIIRS and information-theoretic image quality metrics PREFERRED QUALIFICATIONS * + Experience applying computer vision (CV) and machine learning (ML) techniques to EO imagery to address intelligence problems, This is a Expert-level (Level 5) position requiring a minimum of 18 experience points. Points are calculated as follows: * Education: Associate's = 2 pts · Bachelor's = 3 pts · Master's = +2 pts · PhD = +3 pts * Professional / Military Experience: 1 pt per year of relevant experience * Certifications: 0.5 pts each * Specialized Training: 0.25 pts per relevant course * Professional Impact (publications, presentations, patents): up to 3 pts total, NLP-based Curation Computer Vision [Preferred] ML Techniques [Preferred], You are an experienced EO imagery scientist energized by working at the boundary of remote sensing and machine learning. You want your expertise to directly shape AI/ML training data quality on a consequential national security program - and you're comfortable owning that work technically from day one., This may not be the right fit if you prefer purely analytical or finished intelligence work without hands-on pipeline and preprocessing responsibilities, or if EO sensor phenomenology is not your primary area of expertise. ## Description The Imagery Scientist is the subject matter expert on electro-optical imagery. You'll provide technical direction and conduct the work necessary to acquire and prepare EO imagery of the quality, standards, and requirements the Government specifies - with solutions informed by the specific phenomenology limitations and advantages of each sensor and platform. You'll integrate emerging EO sensors into Maven pipelines, build tiling and conversion pipelines, generate pre-labels, and curate imagery to government-directed priorities. Your work feeds directly into Maven's model development pipeline., The Imagery Scientist is the subject matter expert on their respective imagery modality (e.g., Electro-Optical). They shall provide technical direction and conduct the work necessary to acquire and prepare imagery of the necessary quality, standards, and requirements provided by the Government. Developed solutions should be informed by specific phenomenology limitations and advantages of the sensors and platforms in mind., * *Integrate emerging EO sensors into Maven data pipelines; assess metadata, format, and schema differences and recommend ETL adaptations * *Execute daily EO imagery curation: assess image quality using NIIRS and information-theoretic metrics, prioritize acquisitions per government direction, convert files to required formats (specified imagery formats for unclassified and classified deliverables) * *Tile full-size imagery into precise pixel dimensions or geospatial boundaries, accounting for orthorectification to ensure spatial accuracy at tile edges * *Generate pre-labels from intelligence reporting, machine-derived observations, and human observations - conforming to defined ontology standards to tip and cue human labelers * *Collaborate with the SAR Imagery Scientist to provide coincident EO imagery aligned with SAR collection areas and temporal windows * *Oversee weekly processed imagery deliveries (high-volume curated imagery deliverables on a regular delivery cadence); execute ad-hoc quick-turn deliveries as needed, + Integrate emerging EO sensors and platforms into Maven data pipelines; assess and adapt ETL processes for metadata, format, and schema differences + Develop and implement mathematical conversion models to transform data labels across imagery types (PNG, NITF) and between orthorectified and non-orthorectified imagery + Execute tiling and preprocessing of full-size raw imagery to specified formats and dimensions while maintaining geospatial accuracy and metadata integrity + Analyze and assess image quality and sensor metadata; curate acquisitions in alignment with government-directed priorities using NIIRS and information-theoretic metrics + Generate pre-labels from intelligence reporting and machine- and human-derived observations conforming to defined ontology standards + Identify and implement curation methods - including NLP-based intelligence extraction and automated machine techniques - to maximize high-value imagery yield + Monitor and prioritize data holdings to support data diversity needs (geographic regions, temporal windows, metadata and scene characteristics) + Develop, test, and evaluate new EO algorithms and methodologies using advanced processing tools and cloud-based solutions, + You think in phenomenology - collection geometry, sensor characteristics, and scene conditions are second nature, not references you look up + You can move from scientific analysis to code: writing Python to automate tiling, validate metadata, and build preprocessing workflows + You're rigorous about data integrity - you understand that a tile with bad geospatial bounds corrupts a label, and you build pipelines that prevent it + You adapt quickly when a new sensor arrives with incomplete documentation - you assess, hypothesize, test, and integrate + You communicate your science clearly - whether briefing a program manager or writing documentation another analyst can actually use ## Related Videos - [Leveraging Large Language Models for Legacy Code Translation: Challenges and Solutions](https://www.wearedevelopers.com/videos/1157-leveraging-large-language-models-for-legacy-code-translation-challenges-and-solutions) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Building a hypercar from scratch](https://www.wearedevelopers.com/videos/607-building-a-hypercar-from-scratch) - [WeAreDevelopers LIVE - Building The World’s Worst Image Editor™](https://www.wearedevelopers.com/videos/1836-wearedevelopers-live-building-the-world-s-worst-image-editor) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [6 Emerging Technologies We’ll Learn About in 2025](https://www.wearedevelopers.com/magazine/381-6-emerging-technologies-we-ll-learn-about-in-2025) - [Dev Digest 134 - Where pixels sing?](https://www.wearedevelopers.com/magazine/477-dev-digest-134-where-pixels-sing) - [What Can AI-Generated Images Tell Us About Society’s Biases?](https://www.wearedevelopers.com/magazine/239-what-can-ai-generated-images-tell-us-about-society-s-biases) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past)