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 individual will be responsible for both hands-on annotation work and quality analysis across large-scale datasets that power advanced AI systems.

The ideal candidate enjoys working directly with data, has strong attention to detail, and can balance repetitive annotation tasks with deeper investigations into quality trends, reporting, and process improvement opportunities. This role will partner closely with annotation teams, QA leadership, and product stakeholders to improve the accuracy and reliability of training data used across AI, robotics, and spatial computing initiatives.

Responsibilities

Review and audit annotated datasets to ensure accuracy, consistency, and adherence to quality standards

Investigate data quality issues, identify root causes, and recommend corrective actions

Build and maintain dashboards, trackers, and reports to monitor QA performance and operational health

Write SQL queries and utilize Python to analyze datasets and uncover quality trends

Partner with annotation and operations teams to improve workflows, guidelines, and quality standards

Test new QA, annotation, and workflow tools and provide structured feedback to product and engineering teams

Track key quality metrics and develop recommendations for process improvements

Support quality initiatives across video, image, 3D, and multimodal datasets

Assist with calibration exercises and help maintain consistency across annotation teams

Document findings, trends, and quality insights for leadership and operational stakeholders

Perform hands-on data annotation, labeling, tagging, and quality review activities across multiple data modalities

Validate annotation outputs, identify inconsistencies, and escalate edge cases for review

Maintain productivity and quality targets while executing repetitive, detail-oriented annotation and QA tasks

Support ongoing data preparation efforts that directly contribute to AI, robotics, computer vision, and spatial intelligence model development

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global’s Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

• 2+ years of experience in data annotation, data quality, quality assurance, or AI data operations
• Experience writing and troubleshooting SQL queries
• Working knowledge of Python for data analysis and reporting
• Experience building dashboards using Tableau, Power BI, Looker, or similar BI tools
• Advanced proficiency in Excel and Google Sheets
• Experience working with annotation, labeling, moderation, or QA platforms

Strong analytical thinking and problem-solving abilities

• Excellent attention to detail and ability to identify patterns within large datasets
• Strong written and verbal communication skills - 4+ years of experience in AI data operations, data quality, or annotation programs
• Advanced SQL and Python skills
• Experience supporting AI, machine learning, computer vision, or robotics programs
• Experience working within large-scale technology companies or high-volume data operations environments
• Experience with video, image, 3D, or multimodal datasets
• Exposure to spatial computing, autonomous systems, or robotics data workflows
• Experience creating operational metrics, KPIs, and quality scorecards