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Remote Statistical Process Control Jobs in Virginia

Controls Engineer

Charlottesville, VA · On-site +1

$90K - $125K/yr

This remote position can be located in the Charlottesville, VA area, or surrounding areas or Remote ... Work directly with clients to diagnose and correct system faults, process control issues, and ...

Statistical Analysis & Interpretation:Assists in performing basic descriptive and inferential ... Databricks for data processing and analytics workflows * Epic data structures and reporting ...

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Remote Statistical Process Control information

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

To thrive as a Remote Statistical Process Control Specialist, you need strong analytical skills, a solid understanding of statistics, and experience in quality assurance, often supported by a degree in engineering, mathematics, or a related field. Proficiency with statistical software tools like Minitab, JMP, or SPC modules within ERP systems, as well as familiarity with Six Sigma or similar certifications, is typically required. Attention to detail, problem-solving, and effective remote communication are essential soft skills for interpreting data trends and collaborating with distributed teams. These skills ensure accurate process monitoring, timely quality improvements, and efficient coordination, which are critical for maintaining manufacturing standards remotely.

How does a Remote Statistical Process Control specialist typically collaborate with on-site teams to ensure process quality?

Remote Statistical Process Control (SPC) specialists frequently work with on-site production and quality teams through virtual meetings, shared dashboards, and collaborative data analysis tools. They provide actionable insights by monitoring real-time process data, identifying trends or anomalies, and recommending corrective actions. Effective communication is crucial, as remote SPC specialists must clearly convey findings and support implementation of process improvements. Regular coordination ensures that remote oversight aligns with on-site operational goals and compliance requirements.

What is Remote Statistical Process Control?

Remote Statistical Process Control (SPC) refers to the use of statistical methods and software to monitor, control, and improve manufacturing or business processes from a remote location. By collecting and analyzing data in real time, SPC professionals can detect variations, identify trends, and recommend corrective actions without being physically present at the production site. This approach helps organizations maintain product quality, reduce defects, and improve efficiency, especially in environments where on-site monitoring is not feasible. Remote SPC often involves the use of cloud-based tools and secure data transmission to ensure effective oversight.

What is the difference between Remote Statistical Process Control vs Remote Quality Analyst?

AspectRemote Statistical Process ControlRemote Quality Analyst
CredentialsStatistical certifications, engineering backgroundQuality assurance certifications, analytical skills
Work EnvironmentManufacturing, production settings, data analysisQuality departments, inspection, testing environments
Industry UsageManufacturing, industrial sectorsHealthcare, manufacturing, service industries
Job FocusMonitoring and controlling processes using statistical methodsEnsuring product quality and compliance

Remote Statistical Process Control specialists focus on analyzing manufacturing data to optimize processes, while Remote Quality Analysts concentrate on maintaining product quality standards. Both roles require analytical skills and industry knowledge but differ in their primary objectives and work environments.

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

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • 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.