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Data Labelling Jobs in Virginia (NOW HIRING)

Affixing Labels to cabling and Power Cords * Affix bar coding to equipment * Affix free printed ... The minimum salary for the Union Data Center Installer is $24.84 hourly and the maximum of $26.52 ...

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Data Centre Technician

Ashburn, VA · On-site

$25 - $35/hr

Job Title: Data Centre Technician Location: Data Center- Ashburn, VA, (Multiple Locations ... Route, patch, label, and document fibre-optic and network connections. Support network engineers ...

Create mass labels and apply per Portmap * Differentiate live cables from decom cable * Copper ... The minimum salary for the Union Data Center Technician is $31.46 hourly and the maximum of $32.31 ...

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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.

Data Management / Data Analysis Specialist

Vienna, VA • Remote

Full-time

Posted 18 days ago


Key responsibilities

  • Program and code data-collection instruments, including questionnaires, interview guides, checklists, and scorecards.

  • Perform data quality checks, cleaning, recoding, labeling, and prepare datasets for analysis while maintaining an audit trail.

  • Create data visualizations, tables, and charts for reports, presentations, and stakeholder updates.


Job description

Integrated Business & Technical Consultants, Inc. (IBTCI), a U.S.-based international development consulting company established in 1987, has worked in over 100 countries and implemented over 300 projects. IBTCI serves government agencies, private-sector companies, and donor organizations. IBTCI specializes in monitoring, evaluation, research, and learning (MERL) and institutional support across sectors including conflict and crisis, democracy and governance, agriculture, economic growth, food security, education, environment, and global health.

Assignment Title: Data Management / Data Analysis Specialist

Department/Location: Remote, with possible travel to target countries

Technical Point of Contact: Team Leader

Type: Consultant, Short-term / Intermittent

Classification: Consultancy

Overview: IBTCI is seeking a Data Management / Data Analysis Specialist to support a proposed Livelihoods Framework and Evaluations assignment. The specialist will program and code data-collection instruments; establish secure, well-documented data flows; process incoming qualitative and quantitative data; conduct cleaning, quality control, analysis, and visualization; and support consistent reporting across 13 project evaluations. The role requires careful management of concurrent country datasets and transparent, reproducible analytical workflows.

Essential Duties/Tasks and Responsibilities:

  • Translate approved questionnaires, interview guides, checklists, and scorecards into reliable electronic data-collection instruments using appropriate platforms.
  • Program skip logic, range and consistency checks, required fields, unique identifiers, consent gates, language versions, metadata, and secure submission workflows.
  • Develop and maintain data-management plans, data dictionaries, codebooks, file-naming conventions, access controls, version-control procedures, and data-retention and destruction protocols.
  • Receive, inventory, merge, de-identify, and securely store quantitative and qualitative data from field teams, implementing organizations, and secondary sources.
  • Perform daily or scheduled data-quality checks for completeness, duplication, missingness, outliers, logical inconsistencies, interview duration, enumerator patterns, and protocol deviations; document and resolve queries with field teams.
  • Clean, recode, label, derive, and prepare analysis-ready datasets while preserving raw data and a transparent audit trail of all transformations.
  • Prepare quantitative tabulations and statistical outputs and support qualitative coding, codebook management, retrieval, and thematic analysis.
  • Integrate qualitative and quantitative evidence into triangulation matrices and maintain evidence links supporting scorecard ratings, findings, conclusions, and recommendations.
  • Create clear tables, charts, and other data visualizations for monthly updates, evaluation reports, scorecards, slide decks, and stakeholder presentations.
  • Protect confidentiality and personally identifiable information and comply with approved IRB, consent, safeguarding, data-protection, and implementing-organization requirements.

Minimum Qualifications:

  • At least 5 years of professional experience in evaluation data management, research data processing, quantitative or qualitative analysis, or a closely related function.
  • Demonstrated experience programming or coding electronic data-collection instruments and implementing field validation and skip logic.
  • Experience cleaning, quality-checking, merging, labeling, and documenting multi-source datasets from surveys, interviews, focus groups, checklists, or administrative records.
  • Proficiency in Excel and at least one quantitative analysis package such as SPSS, Stata, R, or Python.
  • Experience with at least one electronic data-collection platform such as KoboToolbox, SurveyCTO, ODK, Qualtrics, REDCap, or a comparable system.
  • Experience with qualitative data coding or qualitative analysis software, or demonstrated ability to manage coded qualitative datasets.
  • Ability to produce accurate, accessible, decision-oriented data visualizations and tables.
  • Strong attention to detail, documentation, data security, and deadline management.
  • Excellent written and oral communication skills in English.

Education: Bachelor's degree in statistics, data science, information systems, economics, social sciences, evaluation, public policy, or another relevant field.

Preferred Knowledge, Skills, and Abilities:

  • Master's degree in a relevant field.
  • Experience supporting multi-country livelihoods, humanitarian, agriculture, food security, or economic-development evaluations.
  • Experience in low-connectivity, multilingual, fragile, or conflict-affected field settings.

Work environment: This position is primarily remote and computer-based and requires secure handling of confidential evaluation data.

Physical Requirements: This position requires the ability to speak, hear, see, use a computer or mobile device, and lift small objects up to 20 lbs. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform essential functions.

Supervisory Responsibility: This position has no supervisory responsibility.

Travel: Limited travel may be required.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this assignment. Duties, responsibilities, and activities may change at any time with or without notice.