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Remote Science Jobs in Woodbridge, VA (NOW HIRING)

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Must have a Advanced Degree (Master s or PhD) in Statistics, Applied Mathematics, Data Science ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Must have a Advanced Degree (Master s or PhD) in Statistics, Applied Mathematics, Data Science ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

DataAnnotation

Data Science Consultant

Washington, DC · On-site +1

$60/hr

AI models are increasingly capable of performing complex analytical and scientific reasoning -- but ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

Skyline Scientific Inc

Senior Data Scientist

Mclean, VA · Remote

$150K - $200K/yr

This role applies physics-based modeling, image science, and data analytics to detect, track, locate, and characterize remote sensing targets. While familiarity with OPIR is valuable, the primary ...

Leidos

Expert Hyperspectral Image Scientist

Springfield, VA · Remote

$116.35K - $210.33K/yr

Bachelor's degree in Remote Sensing, Imaging Science, Physics, Electrical Engineering, Geospatial Science, Applied Mathematics, Computer Science, or a related technical field. * Minimum of 12-15 ...

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Remote Science information

See Woodbridge, VA salary details

$24.2K

$47.9K

$78.1K

How much do remote science jobs pay per year?

As of May 28, 2026, the average yearly pay for remote science in Woodbridge, VA is $47,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,100.00 and $51,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Science professional, and why are they important?

To thrive as a Remote Science professional, you need a strong background in your scientific discipline, analytical skills, and typically a relevant degree or higher qualification. Familiarity with data analysis tools, virtual collaboration platforms, and scientific software such as Python, R, or MATLAB is important. Excellent written communication, time management, and self-motivation are standout soft skills in this remote environment. These abilities ensure effective research, collaboration, and productivity while working independently from various locations.

What are some common challenges faced by professionals working in remote science roles, and how can they be addressed?

Professionals in remote science roles often face challenges such as effective communication across time zones, limited access to lab equipment, and maintaining collaboration with team members. To address these issues, it is helpful to establish regular virtual check-ins, utilize collaborative digital tools, and set clear expectations for project milestones. Many teams also adopt cloud-based data sharing and remote access to specialized software, ensuring that scientific work continues smoothly despite physical distance.

What are remote science jobs?

Remote science jobs are positions in scientific fields that can be performed outside of traditional laboratory or office environments, typically from home or any location with internet access. These jobs may include roles in research, data analysis, scientific writing, consulting, or education. Advances in technology and communication tools have made it possible for scientists to collaborate, conduct experiments, and analyze data remotely. Remote science jobs offer flexibility and can help employers and employees reach a broader talent pool. Common areas include biology, chemistry, environmental science, and healthcare research.

What is the difference between Remote Science vs Remote Data Analyst?

AspectRemote ScienceRemote Data Analyst
Required CredentialsScience degrees, research experience, technical skillsStatistics, data analysis certifications, technical skills
Work EnvironmentResearch labs, academic institutions, remote research projectsBusiness, finance, tech companies, remote data analysis roles
Employer & Industry UsageUniversities, research institutes, biotech firmsCorporations, consulting firms, tech startups
Search & Comparison IntentUnderstanding research roles, scientific projectsData analysis tasks, business insights

Remote Science and Remote Data Analyst roles share a focus on technical skills and remote work environments. However, Remote Science typically involves research, scientific experiments, and academic or biotech settings, while Remote Data Analysts focus on interpreting data for business insights in corporate environments. Both roles require analytical skills but differ in industry application and specific credentials.

What are the most commonly searched types of Science jobs in Woodbridge, VA? The most popular types of Science jobs in Woodbridge, VA are:
What are popular job titles related to Remote Science jobs in Woodbridge, VA? For Remote Science jobs in Woodbridge, VA, the most frequently searched job titles are:
What job categories do people searching Remote Science jobs in Woodbridge, VA look for? The top searched job categories for Remote Science jobs in Woodbridge, VA are:
What cities near Woodbridge, VA are hiring for Remote Science jobs? Cities near Woodbridge, VA with the most Remote Science job openings:
Remote Science jobs near you
Infographic showing various Remote Science job openings in Woodbridge, VA as of May 2026, with employment types broken down into 80% Full Time, 18% Part Time, and 2% Contract. Highlights an 50% Physical, 3% Hybrid, and 47% Remote job distribution, with an average salary of $47,858 per year, or $23 per hour.

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 12 days ago

Job description

Riverside Overview
Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country's most challenging technical problems.
All Riverside Research opportunities require U.S. Citizenship.
Position Overview
Riverside Research's Cognitive Intelligence Solutions Group (CISG) is seeking a Remote Sensing Engineer to support cutting-edge geospatial intelligence, autonomous sensing, and AI/ML-driven data exploitation efforts for the U.S. Department of Defense and Intelligence Community. The successful candidate will serve as a technical lead responsible for the automated verification and validation (V&V), test and evaluation (T&E), and performance assessment of remote sensing data pipelines, AI/ML models, and third-party vendor capabilities. This role bridges rigorous scientific methodology with production-grade engineering, enabling CISG to deliver validated, mission-ready geospatial intelligence products. The ideal candidate combines deep expertise in multispectral and hyperspectral remote sensing with hands-on experience applying machine learning to operational geospatial workflows.
This position is located in Fairfax, VA.
#LI-Onsite
Responsibilities
  • Design, develop, and implement automated V&V and T&E frameworks to assess the accuracy, performance, and operational readiness of remote sensing data products, AI/ML models, and vendor-delivered geospatial capabilities.
  • Lead the technical evaluation of commercial and government remote sensing platforms, sensors (multispectral, hyperspectral, SAR, LiDAR), and associated data products against mission-specific requirements.
  • Develop and maintain scalable, production-grade machine learning pipelines for geospatial applications including change detection, land cover classification, object detection, and environmental monitoring.
  • Apply state-of-the-art AI/ML techniques - including deep learning, transfer learning, self-supervised learning, and large vision/language models - to automate remote sensing data exploitation and analysis workflows.
  • Conduct rigorous uncertainty quantification, validation metric development, and statistical performance benchmarking across multi-source, multi-temporal geospatial datasets.
  • Architect and execute data quality assessment (DQA) protocols for ingested satellite, airborne, and in-situ sensor data; document and communicate findings to program teams and stakeholders.
  • Collaborate with program managers, government customers, and interdisciplinary engineering teams to translate operational requirements into validated technical solutions.
  • Evaluate and integrate emerging remote sensing technologies and open-source AI/ML frameworks; assess vendor claims, algorithm documentation, and technical data packages.
  • Contribute to IRAD initiatives advancing CISG's remote sensing and autonomous sensing capabilities, including development of novel approaches for environmental monitoring, target detection, and geospatial change analytics.
  • Author technical reports, white papers, and briefings documenting methodology, V&V results, and performance findings for government sponsors.
  • Provide technical mentorship to junior engineers and researchers on remote sensing methods, ML best practices, and geospatial data science.
  • Stay current with advances in foundation models, multi-modal geospatial AI, and emerging remote sensing sensor modalities relevant to national security applications.

Qualifications
Required Qualifications:
  • Active U.S. Citizenship (required for all Riverside Research positions).
  • Must be able to obtain and maintain a Top Secret security clearance with SCI access; ability to obtain program-specific clearances as required. Candidates with an active TS/SCI are strongly preferred.
  • Bachelor's degree in Remote Sensing, Geospatial Science, Earth Systems, Electrical Engineering, Computer Science, or a closely related STEM field.
  • A minimum of 8 years of related experience with a Bachelor's degree, 6 years with a Master's degree, 3 years with a PhD, or equivalent combination of education and experience. Graduate research experience counts toward this threshold.
  • Demonstrated expertise in multispectral and/or hyperspectral remote sensing data analysis, including atmospheric correction, spectral indices, spectral unmixing, and feature extraction.
  • Proficiency in Python for geospatial data engineering, including experience with rasterio, rioxarray, xarray, GDAL, geopandas, NumPy, and scikit-learn.
  • Hands-on experience with machine learning and statistical modeling applied to remote sensing or geospatial datasets (e.g., classification, regression, anomaly detection, change detection).
  • Experience developing and executing V&V or T&E processes for data products, software systems, or AI/ML models, including design of test plans, performance metrics, and acceptance criteria.
  • Familiarity with geospatial platforms and tools: ArcGIS Pro, QGIS, ENVI, and/or Google Earth Engine.
  • Experience with cloud-based geospatial workflows (AWS, Google Cloud, or Azure) and version control practices (Git/GitLab/GitHub).
  • Strong written and verbal communication skills with demonstrated ability to present complex technical findings to both technical and non-technical audiences.

Desired / Preferred Qualifications:
  • Active Top Secret/SCI clearance - candidates who already hold an active TS/SCI will be given strong preference and can expect an accelerated onboarding timeline.
  • Experience supporting DoD, Intelligence Community, or national security remote sensing programs (NRO, NGA, AFRL, ARO, or equivalent).
  • Familiarity with hyperspectral sensing platforms (e.g., AVIRIS, PRISMA, orbital hyperspectral systems) and hyperspectral analytics pipelines including mineral characterization and vegetation health assessment.
  • Experience applying deep learning frameworks (PyTorch, TensorFlow, Hugging Face) to geospatial or computer vision tasks, including fine-tuning foundation models or geospatial FMs (e.g., Prithvi, SatMAE, Clay).
  • Background in SAR processing, LiDAR analysis, or multi-modal sensor fusion for environmental or intelligence applications.
  • Experience with automated testing frameworks, CI/CD pipelines, and MLOps practices for geospatial AI/ML systems.
  • Track record of peer-reviewed publication, conference presentations (e.g., IGARSS, AGU, SPIE), or technical reports in remote sensing or geospatial AI.
  • Demonstrated experience in a lead or senior individual contributor role, including mentorship of junior technical staff and coordination across multi-disciplinary teams.
  • Familiarity with GEOINT tradecraft, NSDI standards, or DoD geospatial data standards (NTM, NITF, STANAG imagery formats).

Global Comp
$115,000 - $200,000 This represents the typical compensation range for this position based on experience, location and other factors.
Closing Statement
Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees.
Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran's status or any other status legally protected by applicable federal, state, and local law.

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