Data Annotation Team Leader
3 weeks ago
Key Responsibilities 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.
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