Data Annotation Team Leader

Lead, Train & Empower Global Teams Drive the training and development of overseas data annotators, serving as the go-to expert for daily guidance and Q&A support.

Proactively document recurring challenges, perform root-cause analysis, and implement effective solutions to elevate team performance and consistency. 2.

Turn Feedback into Continuous Improvement Collaborate closely with stakeholders to monitor feedback and acceptance outcomes.

Translate insights into actionable improvements by refining annotation methodologies and enhancing guidelines — ensuring quality standards are not only met but consistently exceeded. 3.

Champion Quality Excellence Design and implement a robust quality control framework that oversees the entire annotation lifecycle.

Establish clear evaluation metrics, conduct comprehensive audits, and safeguard project integrity by preventing substandard data from progressing downstream. 4.

Optimize Processes & Drive Efficiency Anticipate operational risks and identify potential team management challenges before they arise.

Leverage hands-on experience to recommend smart process enhancements and efficiency strategies that strengthen overall project execution. 5.

Deliver with Precision & Accountability Own project timelines and quality benchmarks by strategically planning workloads and coordinating resources effectively.

Ensure high-quality data is delivered on schedule, meeting — and surpassing — client expectations.

Job Requirements: 1.

Education & Experience Bachelor’s degree or higher in a relevant field.

Minimum 2.5 years experience in data annotation is required.

Able to quickly understand project requirements and adapt to operational workflows. 2.

Language Proficiency English is a MUST and Chinese (written and spoken) is preferred.

Able to read and interpret English annotation guidelines and technical documentation accurately.

Capable of supporting data annotation tasks for international projects. 3.

Technical & Analytical Skills Familiar with fundamental data analysis techniques, including descriptive statistics, data cleaning, and preprocessing.

Proficient in using data analysis tools to perform basic analysis on annotated datasets.

Able to provide data-driven insights and recommendations to support annotation quality and decision-making.