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Remote Data Annotation Analyst Jobs in Virginia (NOW HIRING)

ICF is seeking an experienced Data Analytics Manager to lead enterprise data, analytics, governance ... This position is remote within the United States. Please note that ICF monitors employee work ...

Provide consulting relating to the data mining and analysis of data from a range of sources to ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Provide consulting relating to the data mining and analysis of data from a range of sources to ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Perform advanced analysis and produce complex data models, insights, and analytics from our Geo ... Other Info This is a remote position that may require occasional travel. Candidates must reside in ...

New

Junior Data Analyst

Arlington, VA · On-site +1

$50K - $75K/yr

TSTC is seeking a full-time Junior Data Analyst to provide research services for one of TSTC ... Flexible Work Options - Remote work allowed, flexible schedules, and telework opportunities ...

Junior Data Analyst

Arlington, VA · On-site +1

$50K - $75K/yr

TSTC is seeking a full-time Junior Data Analyst to provide research services for one of TSTC ... Flexible Work Options - Remote work allowed, flexible schedules, and telework opportunities ...

The Health IT Data Analyst will develop reports, dashboards, and analytical products that enable ... This is a remote position requiring all work be performed in the continental United States. US ...

Senior Solutions Architect

Arlington, VA · On-site +1

$15K - $165K/yr

... analysis of operational data. * Ensure all design and implementation approaches adhere to the ... Provide secure and stable methods for the remote diagnosis and resolution of maintenance issues ...

Showing results 21-40

Remote Data Annotation Analyst information

What is a remote data annotation analyst?

Remote Data Annotation Analysts are professionals who label, categorize, or tag data—such as images, text, audio, or video—from a remote location. Their work helps train machine learning algorithms by providing structured datasets that computers can learn from. These analysts use specialized tools to identify relevant features in raw data, ensuring accuracy and consistency. The role often requires attention to detail, basic technical skills, and the ability to follow specific guidelines or instructions. This position is commonly found in industries like artificial intelligence, autonomous vehicles, and natural language processing.

What are the key skills and qualifications needed to thrive as a remote data annotation analyst?

To thrive as a Remote Data Annotation Analyst, you need strong attention to detail, analytical thinking, and a high school diploma or equivalent, with many roles preferring experience in data-related tasks. Familiarity with data annotation platforms (like Labelbox or AWS SageMaker Ground Truth) and basic understanding of data management tools are typically required. Excellent time management, self-motivation, and clear communication help analysts manage remote workloads and collaborate effectively with distributed teams. These skills ensure accurate, high-quality annotated data essential for training and validating machine learning models.

How does a remote data annotation analyst typically collaborate with team members and ensure consistent labeling standards?

As a Remote Data Annotation Analyst, you’ll frequently work within a distributed team, using collaboration tools such as Slack, project management platforms, and shared annotation guidelines. Regular virtual meetings and feedback sessions help ensure everyone applies labeling standards consistently and resolves ambiguities. It’s common to review peer annotations and participate in quality assurance checks, promoting a culture of accuracy and continuous improvement. Clear communication and attention to detail are essential for maintaining high-quality annotated datasets across the team.

What is the difference between Remote Data Annotation Analyst vs Remote Data Labeler?

AspectRemote Data Annotation AnalystRemote Data Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentHome-based, flexible hoursHome-based, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnalyzing and verifying labeled data, quality controlLabeling data, annotating images, text, or audio

The main difference is that Remote Data Annotation Analysts focus on verifying and ensuring the quality of labeled data, often involving analysis and review, while Remote Data Labelers primarily perform the task of labeling or annotating raw data. Both roles are essential in AI development and share similar work environments and skill requirements, but their specific responsibilities differ in scope and focus.

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

The most popular types of Data Annotation Analyst jobs in Virginia are:

What are popular job titles related to Remote Data Annotation Analyst jobs in Virginia?

For Remote Data Annotation Analyst jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Data Annotation Analyst jobs in Virginia look for?

The top searched job categories for Remote Data Annotation Analyst jobs in Virginia are:

What cities in Virginia are hiring for Remote Data Annotation Analyst jobs?

Cities in Virginia with the most Remote Data Annotation Analyst job openings:

Infographic showing various Remote Data Annotation Analyst job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Medical Microbiology Consultant - Remote

micro1 AI

Hampton, VA • Remote

$70 - $90/hr

Part-time

Posted 24 days ago


Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.