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Remote Statistical Process Control Jobs (NOW HIRING)

TriOptus LLC

DataOps Engineer

Montpelier, VT · Remote

... processes Implement statistical process control (SPC) and anomaly detection to ensure data ... remote environment Preferred Qualifications Certifications such as: Azure Data Engineer Power BI ...

Vrtx

Principal Statistical Programmer

Boston, MA · Remote

$149.20K - $223.80K/yr

Performs quality control checks of SAS code and output produced by other Statistical Programmers to ... Remote-Eligible Flex Eligibility Status: In this Remote-Eligible role, you can choose to be ...

Fluence Labs

NDT Technician

Houma, LA · Remote

$40 - $60/hr

Perform process control checks & statistical process monitoring * Interface with vendors, tooling and automation groups to define requirements, manage projects through to delivery * Develop and ...

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How much do remote statistical process control jobs pay per year?

As of Jun 3, 2026, the average yearly pay for remote statistical process control in the United States is $72,143.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $77,000.00 per year, depending on experience, location, and employer.

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.

More about Remote Statistical Process Control jobs
What cities are hiring for Remote Statistical Process Control jobs? Cities with the most Remote Statistical Process Control job openings:
What are the most commonly searched types of Statistical Process Control jobs? The most popular types of Statistical Process Control jobs are:
What states have the most Remote Statistical Process Control jobs? States with the most job openings for Remote Statistical Process Control jobs include:
What job categories do people searching Remote Statistical Process Control jobs look for? The top searched job categories for Remote Statistical Process Control jobs are:
Remote Statistical Process Control jobs near you
Infographic showing various Remote Statistical Process Control job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 80% Full Time, 17% Part Time, 1% Contract, and 1% Nights. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $72,143 per year, or $34.7 per hour.
DataOps Engineer

DataOps Engineer

TriOptus LLC

Montpelier, VT • Remote

Full-time

Posted 3 days ago

Job description

Job Title: DataOps Engineer Job Type: Contract Duration: 12 15 months (with potential for extension) Work Location: Remote (U.S.-based) Work Hours: Standard business hours Job Overview We are seeking an experienced DataOps Engineer to support a large scale healthcare data modernization initiative. This role focuses on building and operationalizing modern data quality, governance, analytics, and performance monitoring capabilities within an enterprise data environment. The ideal candidate will combine strong technical expertise with the ability to collaborate closely with internal teams through hands on delivery, documentation, and knowledge transfer.

The engagement emphasizes long term sustainability, staff enablement, and repeatable best practices rather than one time development. Key Responsibilities DataOps and Data Quality Develop and maintain data quality rules, validation frameworks, and monitoring processes Implement statistical process control (SPC) and anomaly detection to ensure data reliability Support incident logging, triage, root cause analysis, and continuous improvement efforts Data Governance and Metadata Define and maintain metadata standards, data glossary entries, and end to end data lineage Establish governance procedures, SOPs, and disclosure/suppression rules Translate downstream analytics and governance requirements into clear upstream data specifications Analytics and Business Intelligence Design and support governed semantic data models Assist with the development and validation of standardized dashboards and reports Ensure data accuracy, refresh reliability, and compliance with governance standards Platforms and Tools Work within platforms such as Azure DevOps, cloud based data lakes, and BI tools Maintain operational dashboards, KPIs, and performance metrics Support agile workflows, documentation repositories, and collaboration tools Enablement and Collaboration Partner with internal teams through hands on co development sessions Create and maintain Wikis, runbooks, and playbooks for long term ownership Deliver role based training and support organizational readiness initiatives Required Qualifications Proven experience as a DataOps Engineer, Data Engineer, Analytics Engineer, or similar role Strong background in data quality engineering, governance, and analytics enablement Experience with: Azure DevOps or similar workflow tools Business intelligence platforms (e.g., Power BI or equivalent) Cloud data platforms (Azure, AWS, or similar) Experience working in Agile or iterative delivery environments Strong documentation, communication, and stakeholder collaboration skills Ability to work independently in a remote environment Preferred Qualifications Certifications such as: Azure Data Engineer Power BI Data Analyst Databricks Data Engineer Data Governance or Data Management certifications Experience in healthcare, public sector, or highly regulated data environments Familiarity with change management and operational enablement practices #DataOps #DataEngineering #CloudData #AzureDevOps #PowerBI #DataGovernance #AnalyticsJobs

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