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Internship Data Annotation Analyst information

How hard is it to get hired by data annotation?

Getting hired as a data annotation analyst generally requires attention to detail, basic computer skills, and familiarity with annotation tools or platforms. Many positions are entry-level and may not require extensive experience, making the role accessible to beginners, though some jobs may prefer knowledge of specific data types or industry standards.

What is a data annotation internship?

A data annotation internship is a temporary position where interns assist in labeling and categorizing data, such as images, text, or videos, to help train machine learning models. Interns typically use annotation tools and develop skills in data quality and accuracy under supervision. This role provides practical experience in data preparation and AI development processes.

What does a data annotation analyst do?

A data annotation analyst is responsible for labeling and categorizing data, such as images, text, or videos, to prepare it for machine learning models. They use tools and follow guidelines to ensure data accuracy and consistency, which is essential for training effective AI systems.

What is the difference between Internship Data Annotation Analyst vs Data Labeling Specialist?

AspectInternship Data Annotation AnalystData Labeling Specialist
CredentialsTypically pursuing or recent graduate in related fieldRelevant certifications or experience preferred
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation companies
Industry UsageCommon in AI, machine learning, and tech industriesUsed across AI, autonomous vehicles, and healthcare sectors

The Internship Data Annotation Analyst is usually an entry-level role for students or recent graduates gaining experience in data annotation. In contrast, Data Labeling Specialists are more experienced professionals focused on accurately labeling data for AI models. Both roles are essential in AI development, but the internship provides learning opportunities, while the specialist role involves more independent work and expertise.

Does data annotation actually pay?

Data annotation analysts are typically paid for their work, with compensation varying based on the project, platform, or employer. Many companies offer hourly rates or per-task payments, and some roles may require specific skills or tools. Payment is generally reliable for those working in paid annotation jobs, especially with established platforms or companies.
What are the most commonly searched types of Data Annotation Analyst jobs in Washington? The most popular types of Data Annotation Analyst jobs in Washington are:
Internship Data Annotation Analyst jobs near you

Senior Imagery Analyst (Data Annotation)

Vantor

Falls Church, VA • On-site

$91K - $115K/yr

Full-time

Posted 21 days ago

Job description

Job Summary:
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. They are seeking a detail-oriented Senior Imagery Analyst (Data Annotation) to guide and improve annotation workflows across EO, SAR, and commercial imagery while performing quality validation efforts and mentoring junior team members.
Responsibilities:
• Provide quality assurance reviews of annotated geospatial imagery
• Train and mentor junior annotators on best practices
• Identify systemic annotation issues and drive corrective actions
• Validate annotation accuracy across multiple formats (bounding boxes, segmentation, center points)
• Collaborate with peers, quality lead, program managers, and other critical partners to align data output with downstream model needs
• Recommend and implement improvements to annotation tools and processes
• Write and maintain annotation guidelines and quality control documentation
Qualifications:
Required:
• U.S. citizenship and active TS/SCI clearance
• 7+ years of experience with EO, SAR, COMINT, and/or commercial imagery analysis and geospatial data annotation
• Proficiency in geospatial software tools (e.g., ArcGIS, QGIS)
• Experience using Remote View, SOCET GXP, and/or Fade/Mist
• Demonstrated leadership in data validation or quality assurance processes
• Experience with object classification, visual QA, and annotation feedback cycles
Preferred:
• Experience supporting government or defense missions
• Familiarity with automated quality metrics or annotation pipelines
• Experience with SAR-specific feature analysis
• Basic scripting or automation (e.g., Python, Jupyter) is a plus
• Prior experience writing SOPs or developing team workflows
Company:
A spatial intelligence firm. Founded in 2025, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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