EO Imagery Scientist

Geo Owl
Springfield, VA, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Transformation Geospatial Intelligence Python (Programming Language) MATLAB Machine Learning

Job description

Support AI-enabled geospatial intelligence by preparing and analyzing electro-optical (EO) imagery for machine learning and operational applications., * Process and curate EO imagery datasets.

  • Develop preprocessing and image tiling workflows.
  • Evaluate imagery quality and metadata.
  • Support labeling campaigns and AI/ML training datasets.
  • Collaborate across teams to integrate new imagery sources.

Requirements

Do you have experience in Remote sensing observations?, * 4+ years of EO imagery analysis experience.

  • Strong understanding of remote sensing principles.
  • Experience with Python, MATLAB, or geospatial processing tools.
  • Familiarity with image preprocessing and data transformation.

Benefits & conditions

Pulled from the full job description

  • Military leave
  • Health insurance
  • 401(k) matching
  • Paid time off
  • Vision insurance
  • Dental insurance
  • Paid military leave, 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

About the company

Our mission is to empower EVERYONE with geospatial technologies.

Geo Owl is a premier provider of geospatial intelligence services, delivering cutting-edge solutions to the Department of Defense, intelligence agencies, and enterprises around the globe. Our comprehensive products and services include advanced geospatial analysis, imagery intelligence, remote sensing analysis, data science, and space-based custom intelligence solutions. At Geo Owl, we are dedicated to leveraging the latest analytic principles and technology to support and enhance the missions of our clients.

Our core values-innovation, integrity, and excellence-drive everything we do. We are committed to pushing the boundaries of geospatial intelligence to ensure our clients receive the most accurate, timely, and actionable intelligence possible. Integrity is at the heart of our operations; we uphold the highest standards of ethics and accountability in our work. Striving for excellence is not just a goal but a standard; we consistently aim to exceed expectations in every project.

Geo Owl’s culture is built on collaboration, continuous learning, and respect. We cultivate an environment where team members can grow both personally and professionally. Our team is composed of passionate, dedicated experts who are always ready to support each other. We value work-life balance, offering flexible working arrangements and a supportive workplace where everyone feels valued.

At Geo Owl, we invest in our employees’ growth and development. We provide ongoing training, career advancement opportunities, and a platform to work on impactful projects that make a real difference. Our team enjoys a strong sense of camaraderie and purpose, knowing that their work contributes to national security and global stability. If you are looking for a dynamic, rewarding career in geospatial intelligence, Geo Owl is the place for you. Join us and be part of a team that is shaping the future of geospatial intelligence.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

4:10 min

Introduction to technical background and geospatial roles

Joana Simoes · LIVE

3:39 min

Introduction to data transformations for machine learning

Alexander Uhlig · WWC 2022

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

2:40 min

Motivations for transitioning legacy MATLAB repositories to Python

Michael Niebisch Michael Niebisch · WWC 2024

3:53 min

Accessing large environmental datasets to analyze global climate challenges

Sohan Maheshwar · LIVE

3:30 min

Transforming data pipelines natively through lightweight serverless functions

Mary Grygleski Mary Grygleski · LIVE

Videos

See all

Related articles

See all