Data Annotation Team Leader

• Lead, coach and mentor a team of data annotators to meet productivity and quality targets.
• Plan, assign and prioritise annotation tasks, manage workflows and scheduling to meet project deadlines.
• Define, review and enforce annotation guidelines, quality standards and best practices to ensure consistency, accuracy and reliability of annotated data.
• Monitor annotation performance metrics (e.g., throughput, accuracy, error rates), generate reports, identify issues/trends and drive corrective actions.
• Collaborate with data scientists, machine learning engineers, product/engineering teams to understand annotation requirements and ensure annotations meet technical/modeling needs.
• Provide training and onboarding for new annotators, continuous development of existing team members (feedback, coaching, one-on-ones).
• Identify process improvements, workflow optimisations, tools or automation opportunities to increase annotation efficiency, quality and scale.
• Manage stakeholder expectations: communicate status, escalate risks/issues, support recruitment/hiring when needed.
• Ensure compliance with data governance, privacy, ethical annotation standards.

Qualifications & Skills

Required:

• Bachelor’s degree (or equivalent) in a relevant discipline (e.g., Data, Computer Science, Linguistics, Ops).
• Experience in data annotation / data labeling / data operations environment.
• Demonstrated people-management experience (leading teams, performance management, coaching).
• Strong organisational and coordination skills; ability to manage multiple workflows and priorities effectively.
• Excellent communication and interpersonal skills; capable of working cross-functionally.
• Strong attention to detail, quality-oriented mindset, good analytical skills to review performance metrics and drive improvement.

Preferred:

• Experience in AI/ML domain (language, vision, speech); familiarity with annotation tools/platforms.
• Experience in process improvement, scaling annotation operations, working with large datasets.
• Experience with vendor/contractor management (if relevant).
• Experience working in fast-moving, dynamic environments, and adapting to shifting priorities.