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Remote Statistical Programmer Jobs in Virginia (NOW HIRING)

Remote/Hybrid Job Type: Full-Time Position Overview: Venesco is seeking a skilled SAS Programmer to ... Bachelor's or Master's degree in Statistics or related field 5+ years of SAS programming experience ...

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Remote Statistical Programmer information

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$83.8K

$146K

$246.9K

How much do remote statistical programmer jobs pay per year?

As of May 29, 2026, the average yearly pay for remote statistical programmer in Virginia is $146,028.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,900.00 and $158,600.00 per year, depending on experience, location, and employer.

What Does a Remote Statistical Programmer Do?

As a remote statistical programmer, you use programming techniques to produce useful data sets from raw data. In this role, you may evaluate the programming needs of each project, use validation techniques to ensure the accuracy of all data sets your programs make, and manage both a database and the operating environment of your software. Remote statistical programmers often work from home and collaborate with other programmers through video calls, voice chat, or remote office software. This job is also known as SAS, which stands for statistical analysis system programming, and companies may advertise under either title.

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

To thrive as a Remote Statistical Programmer, you need strong proficiency in statistics, data analysis, and programming languages like SAS or R, typically supported by a degree in statistics, mathematics, or a related field. Familiarity with statistical software, clinical trial data standards (such as CDISC), and regulatory submission requirements is often necessary. Attention to detail, problem-solving ability, and effective remote communication are essential soft skills for collaborating with cross-functional teams. These competencies ensure high-quality data analysis, regulatory compliance, and seamless teamwork in a remote environment.

How do Remote Statistical Programmers typically collaborate with cross-functional teams despite working remotely?

Remote Statistical Programmers often work closely with biostatisticians, data managers, and clinical research associates using collaborative tools such as video conferencing, project management platforms, and secure data-sharing systems. Regular virtual meetings are scheduled to discuss project progress, address data or programming issues, and align on analysis plans. Clear documentation and version control are essential to ensure seamless teamwork and maintain data integrity. Effective communication skills and proactive updates help bridge the physical distance and contribute to successful project outcomes.

What is a remote statistical programmer?

A remote statistical programmer is a professional who uses statistical software and programming languages to analyze data, typically for research, clinical trials, or business insights, while working from a location outside of a traditional office environment. They are responsible for managing, cleaning, and organizing large datasets, and for developing programs that generate statistical analyses and reports. Remote statistical programmers often collaborate with statisticians, data scientists, and project teams using online communication tools. This role requires strong skills in programming languages such as SAS, R, or Python, and attention to detail when handling complex data. Working remotely provides flexibility but also requires good time management and communication skills.

What is the difference between Remote Statistical Programmer vs Clinical Data Analyst?

AspectRemote Statistical ProgrammerClinical Data Analyst
Required CredentialsBachelor's/Master's in Biostatistics, Statistics, or related field; programming skills in SAS, R, or PythonBachelor's/Master's in Statistics, Data Science, or related; strong analytical and statistical skills
Work EnvironmentRemote or office-based, collaborating with biostatistics teams in clinical trialsRemote or on-site, analyzing clinical data to support study outcomes
Employer & Industry UsagePharmaceuticals, biotech, CROs, clinical research organizationsPharmaceuticals, healthcare, research institutions, CROs

Remote Statistical Programmers focus on programming and data management for clinical trials, while Clinical Data Analysts interpret and analyze clinical data. Both roles require strong statistical skills and often work in similar environments within the healthcare and pharmaceutical industries, but their core responsibilities differ.

What are the most commonly searched types of Statistical Programmer jobs in Virginia? The most popular types of Statistical Programmer jobs in Virginia are:
What are popular job titles related to Remote Statistical Programmer jobs in Virginia? For Remote Statistical Programmer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Statistical Programmer jobs in Virginia look for? The top searched job categories for Remote Statistical Programmer jobs in Virginia are:
What cities in Virginia are hiring for Remote Statistical Programmer jobs? Cities in Virginia with the most Remote Statistical Programmer job openings:

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA โ€ข On-site, Remote

$150K - $180K/yr

Full-time

Posted 14 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.