Data Annotator

3 days ago

Central Region, Singapore X Star Technology Pte Ltd Full time $30,000 - $60,000 per year

Key Responsibilities

  • Review and label various types of data — such as text, images, video, or audio — according to detailed annotation guidelines.
  • Ensure accuracy and consistency of labels across large datasets to maintain high data quality.
  • Follow project-specific instructions for labeling categories, attributes, or relationships.
  • Validate and cross-check annotated data for correctness and completeness before submission.
  • Collaborate with QA (quality assurance) and team leads to resolve ambiguities and improve annotation rules.
  • Provide feedback on labeling tools, workflows, and documentation to improve efficiency.
  • Maintain confidentiality and comply with data security and privacy policies.
  • Meet daily or weekly productivity and accuracy targets.
  • Participate in training sessions to stay updated on evolving guidelines and AI model needs.

Required Qualifications

  • Bachelor's degree in Computer Science/AI
  • Strong reading comprehension and communication skills in the project's language(s).
  • Excellent attention to detail and ability to focus on repetitive tasks with precision.
  • Basic computer literacy — ability to use web-based tools, spreadsheets, and annotation interfaces.
  • Ability to follow written instructions and adapt to changing project requirements.
  • Comfortable working with sensitive or challenging content, when applicable (subject to project type).

Preferred Qualifications

  • Prior experience in data annotation, content moderation, transcription, or quality assurance.
  • Familiarity with machine learning or AI concepts (text classification, object detection, speech tagging, etc.).
  • Experience using annotation tools such as Labelbox, SuperAnnotate, Scale AI, Prodigy, Label Studio, or similar platforms.
  • Background in linguistics, computer science, psychology, or cognitive science is a plus (for language-based tasks).
  • Multilingual skills (for multilingual NLP or translation projects).

Key Skills

  • Accuracy and attention to detail
  • Data organization and consistency
  • Time management and task prioritization
  • Basic technical proficiency
  • Communication and teamwork

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