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.