Imagery Scientist (EO)

Geo Owl • Springfield, VA

1d

About The Position

Electro-optical imagery tells a story — but only to someone who understands the sensor, the collection geometry, the phenomenology, and how to turn raw pixels into analytically actionable products. As the EO Imagery Scientist on NGA Maven, your expertise directly shapes the quality of AI/ML training data that informs national security decisions.

Role Overview
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.

Source-Derived Role Summary
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.

A Day in the Life
✓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

Why This Role Matters
Mission Impact
The EO data you curate, tile, and pre-label becomes the training corpus for NGA Maven's AI/ML models. The precision of your science determines the quality of model outputs that support real-world intelligence operations.
Geo Owl Impact
As a Key Position, your technical performance defines Geo Owl's reputation for EO expertise on Maven and strengthens our standing as a mission-first geospatial partner.
Your Growth
You'll work at the cutting edge of applied EO science — integrating pre-IOC sensors, developing novel preprocessing pipelines, and expanding expertise into computer vision and ML data workflows in a high-consequence environment.

Core Responsibilities
▸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

Required Qualifications
✓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

Experience Point Requirement
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

Tools, Technologies & Tradecraft
Python MATLAB Google Earth Engine EO Phenomenology NIIRS PNG / NITF / TIFF ETL Pipelines Orthorectification NLP-based Curation Computer Vision [Preferred] ML Techniques [Preferred]

What Makes Someone Successful in This Role
▸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

Is This Role For You?
✔ Great Fit
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.
✘ May Not Be For You
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.

Career Growth & Professional Value
This role builds deep expertise at the intersection of EO science, AI/ML data engineering, and national security GEOINT. You'll gain hands-on experience integrating emerging sensors in pre-IOC environments, developing production-grade preprocessing pipelines, and contributing to a program that advances the state of the art in overhead imagery exploitation. The combination of scientific depth and applied pipeline engineering experience is rare — and highly valued across the intelligence and defense community.

Requirements

• 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

Nice To Haves

• Experience applying computer vision (CV) and machine learning (ML) techniques to EO imagery to address intelligence problems

Responsibilities

• 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

Benefits

• Health Insurance (Geo Owl pays 80%+ of the premium).
• 401k matching.
• Dental, Vision, and other supplemental insurance plans available.
• Company-paid short-term and long-term disability and life insurance.
• Peer-to-Peer spot bonuses.
• 120 hours of PTO per year plus federal holidays.
• Fully Paid Military Leave: You make your full Geo Owl salary while you are on military duty

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree