Data Quality Analyst

Data Quality Analyst Insight Global is seeking a Data Quality Analyst to support a rapidly scaling AI data operations program focused on computer vision, robotics, and spatial intelligence. This role combines hands-on data annotation with quality analysis across large-scale datasets used to train advanced AI systems. The ideal candidate is detail-oriented, comfortable working directly with data, and able to balance repetitive annotation work with deeper analysis of quality trends and process improvements. This person will work closely with annotation teams, QA leadership, and product stakeholders to improve the accuracy, consistency, and reliability of training data. Responsibilities: Perform hands-on data annotation, labeling, tagging, and quality review across video, image, 3D, and multimodal datasets Review and audit annotated datasets for accuracy, consistency, and adherence to established quality standards Validate annotation outputs, identify inconsistencies, and escalate edge cases for further review Investigate data quality issues, identify root causes, and recommend corrective actions Use SQL and Python to analyze datasets and identify quality trends and opportunities for improvement Build and maintain dashboards, trackers, and reports to monitor quality metrics and operational performance Partner with annotation and operations teams to improve workflows, guidelines, and quality standards Support calibration exercises to maintain consistency across annotation teams Test new annotation, QA, and workflow tools and provide structured feedback to product and engineering teams Document quality findings, trends, and recommendations for leadership and operational stakeholders Maintain established productivity and quality targets while completing detail-oriented annotation and QA work Support ongoing data preparation efforts for AI, robotics, computer vision, and spatial intelligence applications Insight Global