Data Labeling Specialist

Key Responsibilities • Annotate and classify operational datasets, including specific modalities, using approved taxonomies, metadata standards, and task-specific instructions.

• Prepare and organize labeled datasets for use within existing AI platforms and applications.

• Review annotations for accuracy, completeness, consistency, and adherence to approved labeling conventions.

• Identify, document, and resolve data discrepancies, ambiguous records, duplicate entries, and inconsistent labels; elevate 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 the refinement of annotation instructions, review checklists, and repeatable data quality workflows.

• Handle data in accordance with applicable government security, access, and information management requirements.

Required Qualifications • 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 apply labeling guidelines, metadata conventions, and documented quality standards consistently.

• 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 Security Clearance Required: Secret or higher

Desired Qualifications • 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 use in 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.