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Remote Analytics Engineer Jobs in Virginia (NOW HIRING)

Conflux Systems Inc

AI Engineer

Richmond, VA · On-site +1

$52.88/hr

... Remote Need Occationsal Onsite Visit Pay rate: $52.88/hr on W2 Job Summary: The AI Engineer III is responsible for advanced analytics applying statistical, mathematical, and computational models to ...

Ad Hoc

Data Engineer III

Mclean, VA · Remote

$115.70K - $139K/yr

Data Engineer III This is a remote position. Ad Hoc is a technology company that empowers ... Ability to create accurate and accessible datasets for Data Analysts and Scientists to interpret ...

ICF

Manager, Data Analytics - Remote

Reston, VA · Remote

This position is remote within the United States. Please note that ICF monitors employee work ... Partner with cybersecurity, engineering, product, and program management teams to align data ...

CGI Inc.

Remote Support Engineer, Junior

Arlington, VA · On-site +1

Remote Support Engineer, Junior Category: Service Desk / End User Services Main location: United ... Ability to analyze problems, identify solutions, and guide users through the resolution process ...

Staffed4U

Senior Software Engineer

Chantilly, VA · On-site +1

$126.60K - $166.90K/yr

Analyze software and system requirements to develop technical solutions that meet operational ... Hybrid Work Environment Flexible work arrangements may include a combination of remote and onsite ...

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$45.1K

$92.4K

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How much do remote analytics engineer jobs pay per year?

As of Jun 1, 2026, the average yearly pay for remote analytics engineer in Virginia is $92,380.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,400.00 and $117,000.00 per year, depending on experience, location, and employer.

What is a Remote Analytics Engineer job?

A Remote Analytics Engineer is responsible for designing, building, and maintaining the data infrastructure that enables data-driven decision-making. They work with data pipelines, ETL processes, and data warehouses to ensure accurate and efficient data flow. This role typically requires expertise in SQL, Python, and data modeling, as well as experience with cloud platforms and analytics tools. Since the position is remote, strong communication and collaboration skills are essential for working with distributed teams.

What are the key skills and qualifications needed to thrive in the Remote Analytics Engineer position, and why are they important?

To thrive as a Remote Analytics Engineer, you should have a strong background in data analysis, data engineering, and statistical modeling, usually supported by a degree in computer science, statistics, or a related field. Expertise in tools like SQL, Python, R, cloud platforms (such as AWS or Google Cloud), and experience with data visualization tools or certifications (e.g., Google Data Analytics) are typically required. Excellent communication, problem-solving abilities, and self-motivation are vital soft skills for effective remote collaboration and delivering analytical insights. These competencies ensure you can manage complex data pipelines, work seamlessly with distributed teams, and provide actionable results that support business decisions.

What are the main challenges faced by Remote Analytics Engineers, and how are they overcome?

Remote Analytics Engineers often encounter challenges such as coordinating across different time zones, maintaining clear communication with team members, and managing large datasets securely from a distance. These are typically addressed by leveraging collaboration tools (like Slack, Jira, or Zoom), following best practices in data security, and setting consistent check-in routines with the team. Additionally, remote engineers often use robust documentation and automated workflows to ensure data quality and project transparency. Building strong relationships and staying proactive in communication helps pave the way for successful collaboration and project delivery.
More about Remote Analytics Engineer jobs
What are the most commonly searched types of Analytics Engineer jobs in Virginia? The most popular types of Analytics Engineer jobs in Virginia are:
What are popular job titles related to Remote Analytics Engineer jobs in Virginia? For Remote Analytics Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Analytics Engineer jobs in Virginia look for? The top searched job categories for Remote Analytics Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Analytics Engineer jobs? Cities in Virginia with the most Remote Analytics Engineer job openings:
Remote Analytics Engineer jobs near you
Infographic showing various Remote Analytics Engineer job openings in Virginia as of May 2026, with employment types broken down into 9% Internship, 78% Full Time, and 13% Part Time. Highlights an 100% Remote job distribution, with an average salary of $92,380 per year, or $44.4 per hour.

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 16 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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