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Data Labelling Jobs in Virginia (NOW HIRING)

Data Architect - TS/SCI

Rosslyn, VA · On-site

$72.75 - $93.75/hr

This role focuses heavily on data tagging, labeling, governance, lifecycle management, and compliance across the DoW SAP enterprise. The ideal candidate will have strong experience designing and ...

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

Showing results 21-40

Data Labelling information

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.

What are the most commonly searched types of Data Labelling jobs in Virginia?

The most popular types of Data Labelling jobs in Virginia are:

What are popular job titles related to Data Labelling jobs in Virginia?

For Data Labelling jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Data Labelling jobs in Virginia look for?

The top searched job categories for Data Labelling jobs in Virginia are:

What cities in Virginia are hiring for Data Labelling jobs?

Cities in Virginia with the most Data Labelling job openings:

Infographic showing various Data Labelling job openings in Virginia as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

ZERO TRUST (ZT) DATA SUBJECT MATTER EXPERT

Arlington, VA • On-site

$99K - $125K/yr

Full-time

Re-posted 23 days ago


Key responsibilities

  • Provide senior-level advisory guidance on assessing and advancing the agency's enterprise data classification, data governance, and data access control posture in support of Zero Trust Architecture implementation.

  • Conduct comprehensive gap analyses of existing agency data schemas, access policies, and governance practices against ZTMM v2.0 Data pillar criteria, and develop recommended enhancements.

  • Support the development and continuous improvement of the agency's ZT Common Control Catalog, ZT Roadmap, and Implementation Plan related to data-layer controls and maturity indicators.


Job description

ZERO TRUST (ZT) DATA SUBJECT MATTER EXPERT POSITION OVERVIEWThe Zero Trust Data Subject Matter Expert (ZT Data SME) exists to provide senior-level advisory expertise in assessing, analyzing, and advancing the agency's enterprise data security and data governance posture in alignment with Zero Trust Architecture (ZTA) principles. This role serves as the program's authoritative advisory voice on the Data pillar of the CISA Zero Trust Maturity Model v2.0 (ZTMM v2.0), translating federal ZT mandates, including OMB M-22-09, EO 14028, and NIST SP 800-207, into recommended data classification, data access control, and data governance frameworks for agency consideration and concurrence. All advisory products produced by this position are subject to TSA review and concurrence prior to any agency action. DUTIES & RESPONSIBILITIESGeneral DutiesProvide senior advisory guidance on the assessment and advancement of the agency's enterprise data classification, data governance, and data access control posture in support of Zero Trust Architecture implementation.Continuously monitor the federal ZT policy and regulatory landscape, including EOs, OMB memoranda, NIST publications, CISA guidance, and NSA Zero Trust Implementation Guidelines (ZIGs), as they relate to data-layer security requirements; develop recommended updates to program advisory positions for leadership review.Conduct comprehensive gap analyses of existing agency data classification schemas, data access policy frameworks, and data lifecycle governance practices against CISA ZTMM v2.0 Data pillar criteria; develop recommended enhancement approaches for agency concurrence.Provide advisory support for the development and continuous maturation of the agency's ZT Common Control Catalog, with specific focus on data-layer control mappings to NIST SP 800-53 Rev. 5 control families and CISA ZTMM v2.0 Data pillar maturity indicators.Develop recommended updates to the ZT Roadmap and Implementation Plan, incorporating data pillar maturity advancement priorities and data governance enhancement recommendations for agency review.Apply real-time analysis of data access telemetry, CDM data-layer indicators, and behavioral risk signals to proactively surface emerging data exposure vectors and recommend advisory responses for agency consideration.Collaborate with cross-functional ZT pillar SMEs to validate data policy outcomes and provide recommended approaches ensuring data layer integration across Identity, Devices, Networks, and Applications & Workloads pillar assessments.Support all internal and external ZT data calls, requests, audits, and compliance updates related to the Data pillar; ensure recommended responses align with CISA ZTMM v2.0 criteria and applicable federal mandates.Develop recommended new and revised data governance policy documents and data security SOPs; all final documentation requires TSA concurrence prior to issuance.Provide senior advisory support to ZT leadership on data pillar planning, scheduling, solution development, reporting, and integration activities as directed by the ZT SME Team Leader.Leverage AI-assisted analysis tools, automation platforms, and prompt engineering techniques to enhance the efficiency, depth, and quality of data pillar advisory assessments and deliverables.Subject Matter Expertise (SME) Area #1 – Zero Trust Data Classification, Governance & Access ControlExpert-level mastery of CISA ZTMM v2.0 Data pillar maturity criteria with demonstrated ability to conduct authoritative gap assessments and recommend targeted advancement strategies.Authoritative knowledge of federal data security mandates including OMB M-22-09, EO 14028, NIST SP 800-207, NIST SP 800-53 Rev. 5, and applicable FISMA requirements as they relate to data classification, data access, and data lifecycle governance.Demonstrated capability to lead enterprise-scale data classification and data governance assessment efforts in a federal environment; ability to translate policy requirements into operationally actionable recommended frameworks.Expert-level proficiency in data-layer ZT control assessment, including attribute-based access control (ABAC), policy-based access control (PBAC), data labeling and tagging implementations, DLP capability maturity, and CASB integration assessment.Independent advisory judgment on data classification schema design, data access policy framework development, and CDM data-layer telemetry coverage assessment.Problem-solving at the intersection of data governance policy and operational data security implementation; ability to diagnose data-layer ZT maturity gaps and develop recommended remediation pathways that are technically sound and agency-achievable.SME Area #2 – Enterprise Data Security Architecture & Technical Domain FluencyFoundational working knowledge of enterprise data security architectures including cloud data platforms (Azure, AWS, GCP), hybrid cloud data environments, data warehouse and data lake security configurations, and SaaS data protection mechanisms.Familiarity with enterprise data security tooling including DLP platforms, CASB solutions, SIEM data-layer analytics, and CDM program data telemetry capabilities and their intersection with ZT Data pillar maturity advancement.Understanding of encryption at rest and in transit implementation patterns, key management practices, and data sovereignty considerations as they relate to ZT data access control policy application.Supports primary ZT data advisory function by enabling cross-domain assessment that spans the full data lifecycle from data creation and classification through access, sharing, retention, and disposal across diverse TSA system types.Interacts directly with pillar SMEs (Identity, Network, Devices, Applications & Workloads) to validate data-layer policy integration and ensure recommended data access control frameworks are operationally coherent across all CISA ZTMM v2.0 pillars.QUALIFICATIONSMinimum RequirementsA minimum of 10 years of IT cybersecurity experience, including direct support to U.S. Government programs in a data security, information assurance, or ZT advisory capacity.Expert knowledge of NIST SP 800-207, NIST SP 800-53 Rev. 5, FISMA, and federal ZT mandates including OMB M-22-09 and EO 14028 as applied to data classification and data access governance.Demonstrated ability to lead data security and data governance advisory assessments directly supporting ZT Data pillar implementation in a federal environment.Experience developing or maturing enterprise ZT artifacts including Data pillar assessments, data classification schemas, data governance frameworks, and ZT Common Control Catalog data-layer mappings.Proven experience translating federal ZT and data security mandates into actionable agency-level data policy frameworks, data access process changes, and governance control recommendations.Experience supporting or leading ZT-related IG CIGIE metrics reporting or FISMA ZT compliance submissions as they relate to Data pillar requirements.Superb written and oral communication skills; demonstrated ability to navigate highly political client environments and deliver advisory products that reflect agency priorities and sensitivities.Demonstrated familiarity with AI-assisted analysis tools or prompt engineering; ability to apply AI-enabled capabilities to enhance data classification assessment, telemetry analysis, and advisory deliverable development.Preferred QualificationsPrior direct involvement in a federal ZT pilot program or enterprise ZT deployment in a planning, advisory, or assessment capacity with specific data pillar accountability.Experience developing or significantly maturing a ZT Common Control Catalog aligned to NIST SP 800-53 Rev. 5 with Data pillar control inheritance classification.Familiarity with SAFe for Government (SGP) or equivalent agile delivery methodology in a federal program environment.Experience with IG CIGIE audit preparation and response in the context of federal ZT or FISMA compliance, specifically related to data security metrics.CompetenciesTechnical: CISA ZTMM v2.0 (Data pillar), NIST SP 800-207, NIST SP 800-53 Rev. 5, RMF, FISMA, IG CIGIE ZT metrics, DLP/CASB/SIEM platforms, ABAC/PBAC frameworks, CDM data telemetry, data classification methodologies.Leadership: Senior advisory engagement with CISO-level and senior federal leadership; ability to bridge data security policy requirements and operational implementation advisory needs; cross-pillar SME coordination.Behavioral: Proactive data risk identification and real-time advisory posture; political acumen in complex federal stakeholder environments; precision in policy documentation and advisory product development.Education & CertificationsMinimum of a Bachelor of Science (or higher) in Information Technology, Computer Science, Cybersecurity, Information Systems, or a closely related field.Required: Certified Information Security Manager (CISM) or Certified Information Systems Security Professional (CISSP).Strongly preferred: Certified Data Privacy Solutions Engineer (CDPSE); Certified Information Privacy Manager (CIPM); or Certified Chief Information Security Officer (CCISO). Project Management Professional (PMP) or Certified Authorization Professional (CAP/CGRC) also strongly preferred.WORK LOCATIONHybrid – Primarily Remote. Occasional onsite work required at the client location in Springfield, VA. Schedule subject to change based on client requirements.HOURS OF OPERATIONBusiness Hours: 8:00 AM EST – 4:30 PM EST.Core Hours: 9:00 AM EST – 3:00 PM EST.REPORTING STRUCTUREReports To: ZT SME Team LeadDirect Reports: