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Data quality is at the heart of everything we do. Here’s how it works:

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Review layers

Tasks typically go through multiple quality checks:
  1. You create the task following guidelines
  2. Peer reviewers check your work for accuracy and guideline adherence
  3. Operations team may conduct additional quality checks
  4. Client review (in some pipelines) provides final approval

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Feedback process

When reviewers find issues, you’ll receive feedback via:
  • Slack DMs or group chats with your lead
  • Platform comments on specific tasks
  • General guidance shared in team channels
This feedback helps you improve and maintain high quality. We’re all learning together!

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Performance tracking

Your work is tracked to ensure consistency:
  • Task quality scores based on review results
  • Time per task to identify efficiency patterns
  • Guideline adherence to maintain standards
If your performance needs improvement, your pipeline lead will reach out with specific guidance.