Data Labeling Specialist

NextGen Federal Systems • Aberdeen, MD

6d

About The Position

NextGen Federal Systems is seeking a detail-oriented Mid-Level Data Labeling Specialist to support Artificial Intelligence Operations (AIOPS) initiatives within the Next Generation Command and Control (NGC2) environment. The role prepares, annotates, categorizes, and validates structured and unstructured data for use in existing AI platforms and operational applications. The position supports the accurate, consistent, and traceable organization of data for operational workflows and user requirements.

The specialist applies defined labeling standards independently and collaborates with technical personnel, functional subject matter experts, and government stakeholders to clarify data requirements and resolve quality issues. The role requires an active Secret or higher security clearance and handling data according to applicable government security, access, and information management requirements.

Requirements

• Bachelor’s degree in Information Systems, Data Analytics, Computer Science, or a related discipline; equivalent relevant experience may be considered.
• 3–5 years of relevant experience in data labeling, data annotation, data quality assurance, data management, or comparable data operations.
• Demonstrated experience reviewing, categorizing, and validating structured or unstructured datasets.
• Ability to consistently apply labeling guidelines, metadata conventions, and documented quality standards.
• Experience identifying data discrepancies and documenting corrective actions.
• Proficiency with spreadsheet applications and common data organization tools.
• Strong attention to detail, analytical judgment, and organizational skills.
• Ability to work independently while coordinating with technical teams and nontechnical subject matter experts.
• Strong written and verbal communication skills.
• Active Secret security clearance or higher.

Nice To Haves

• Experience supporting DoD or other government data operations programs.
• Familiarity with data annotation or labeling platforms such as Label Studio, CVAT, or comparable tools.
• Experience preparing data for existing AI-enabled applications or operational analytics platforms.
• Familiarity with metadata management, controlled vocabulary, taxonomies, and dataset versioning.
• Experience with quality sampling, annotation agreement checks, and repeatable data review processes.
• Familiarity with CSV, JSON, SQL, or other common data formats and query tools.
• Experience working in controlled-access or secure government computing environments.

Responsibilities

• Annotate and classify operational datasets using approved taxonomies, metadata standards, and task-specific instructions.
• Prepare and organize labeled datasets for existing AI platforms and applications.
• Review annotations for accuracy, completeness, consistency, and compliance with approved labeling conventions.
• Identify, document, and resolve data discrepancies, ambiguous records, duplicate entries, and inconsistent labels; escalate unresolved cases to appropriate subject matter experts.
• Coordinate with technical teams and functional subject matter experts to clarify labeling criteria and data interpretation.
• Perform first- and second-pass quality reviews using defined sampling plans, acceptance criteria, and annotation-agreement measures; document findings and complete required rework.
• Maintain data-labeling records, change history, quality findings, and supporting documentation to preserve traceability.
• Support refinement of annotation instructions, review checklists, and repeatable data quality workflows.
• Handle data in accordance with applicable government security, access, and information management requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level