Data Annotator
@ Taskify

Hybrid
$84,000
Hybrid
Part Time
Posted 7 hours ago

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XXXXXXXX XXXXXXXXX XXXXXXXX***** @taskify.com
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Job Details

About the Role

Join Taskify as a Data Annotator to support groundbreaking AI research. In this remote role, you will label and categorize diverse datasets to improve AI system accuracy.

Key Responsibilities

  • Review and synthesize information from large data volumes.
  • Annotate and categorize text, images, and various data types.
  • Apply guidelines, rubrics, and taxonomies for structured outputs.
  • Identify and flag inconsistencies or errors in datasets.
  • Collaborate with research teams to enhance model performance.

Qualifications / Skills Required

  • Strong analytical thinking and critical reasoning.
  • Excellent written communication and attention to detail.
  • Ability to structure complex or high-volume information.
  • Experience in data annotation or labeling projects is preferred.
  • Must be based in the United States.

Work Location

This is a remote role (U.S.-based only) with flexible, asynchronous working hours.

Key skills/competency

  • Data Annotation
  • Labeling
  • Taxonomy
  • Data Categorization
  • Analytical Thinking
  • Detail-oriented
  • Communication
  • Remote Work
  • Critical Reasoning
  • Collaboration
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How to Get Hired at Taskify

🎯 Tips for Getting Hired

  • Customize your resume: Highlight data annotation and analytical skills.
  • Showcase remote work: Emphasize experience with asynchronous roles.
  • Research Taskify: Understand company mission and project goals.
  • Prepare examples: Demonstrate taxonomy and labeling projects.

📝 Interview Preparation Advice

Technical Preparation

Review data labeling software tutorials.
Practice applying annotation guidelines.
Study rubric and taxonomy examples.
Familiarize with common data formats.

Behavioral Questions

Describe a challenging data task solved.
Explain your approach to detail-oriented work.
Discuss handling ambiguity in data projects.
Share your experience with remote teamwork.

Frequently Asked Questions