Team Lead

1. Team Supervision
   • Lead supervise and motivate a team of AI annotators.
   • Assign daily annotation tasks and monitor workload distribution.
   • Track team attendance productivity and performance.
   • Conduct regular team meetings and provide updates.

• Review completed annotation tasks for accuracy and consistency.
• Perform quality checks (QA) before submission to clients.
• Ensure adherence to annotation guidelines and project requirements.
• Identify annotation errors and provide corrective feedback.
• Maintain project quality targets and accuracy standards.

• Coordinate project activities to ensure timely completion.
• Monitor project progress against deadlines and milestones.
• Escalate technical or operational issues to project managers.
• Ensure resources are available to meet project demands.
• Prepare daily weekly and monthly progress reports.

• Train new annotators on annotation tools guidelines and best practices.
• Conduct refresher training sessions when project guidelines change.
• Mentor team members to improve annotation quality and productivity.
• Support continuous learning and professional development.

Monitor key performance indicators (KPIs) such as:

Annotation accuracy

Productivity

Turnaround time

Error rate

Quality score

• Conduct performance reviews and recommend improvement plans.
• Recognize and reward high-performing team members.

• Act as the primary point of contact between annotators and project managers.
• Communicate project updates changes and client feedback.
• Address team concerns and resolve operational issues promptly.
• Facilitate collaboration across teams.

• Identify workflow inefficiencies and recommend improvements.
• Help develop and update annotation guidelines.
• Implement best practices to improve quality and productivity.
• Participate in pilot projects and process testing.

• Ensure confidentiality of client data.
• Enforce compliance with company policies and data protection requirements.
• Monitor adherence to security protocols and ethical standards.

• Maintain records of completed tasks and quality metrics.
• Generate productivity and quality reports.
• Document recurring issues and proposed solutions.
• Track project risks and mitigation actions.

Bachelors degree in Computer Science Information Technology Data Science Business or related field.

3 years experience in AI data annotationdata labelling or related operations environment with at least 1 year in a supervisory or team leadership role.

Proven experience managing teams monitoring performance and delivering projects within strict deadline and quality standards.

Strong understanding of quality assuarance processes performance metrics and continuous process improvement.

Excellent leadership communication problem solving coaching and stakeholder management.