
DataAnnotation Ml Data Annotator / Labeler Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 10 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at DataAnnotation.
AI Data Labeler
The process was quick and easy, entirely automated. It involved a multiple-choice test and a few open-ended questions to gauge aptitude for the role. Overall, it was a positive experience. The only downside was not hearing about the outcome; I simply checked the site one morning and had access to the projects.
No confirmed questions were included in this interview report.
AI Data Annotator
I didn't have a formal interview, but I did have to complete some assessments. They tested my reading comprehension, writing abilities, and how well I could categorize things. A few weeks after I finished the assessments, they let me know I was accepted and I could start working on projects.
- Using the following three random topics, write a creative story.
AI Data Annotator
The interview process was initially enjoyable, making me eager to contribute to the company. However, a lack of communication and a high volume of applications have led to disillusionment about hearing back. The initial stage involved creative tasks, like writing an original story about an octopus, with strict instructions against using AI. This was followed by a two-part assessment. The first part required interacting with AI bots, choosing a topic (either general chat or coding-related, with no indication of preference), and rating the AI's responses based on provided documentation. The second part involved evaluating two pre-written responses and flagging any that contained errors, harmful content, or misinformation. After completing these tasks, a message confirmed the application submission and stated that further contact would be via email if the application progressed. Unfortunately, it seems my application ended up in the group that completes the initial assessment but receives no further communication. Research suggests a potential two-week waiting period for application review, which has passed. Additionally, job listings indicate over 5000 applications for similar roles, suggesting a competitive landscape. Without any formal rejection or communication from the company, and given their notoriously unresponsive support, it's unclear what could have been done differently or if my application was even reviewed. The only positive aspect was receiving payment for the completed tasks. The company's advertising seems overly optimistic and doesn't reflect the low probability of advancing in the application process, which is unfortunate as I could envision contributing significantly if I had progressed.
- Write a story about a dancing green octopus, set on November 21st. Ensure the answer is not AI-generated.
DataAnnotation Ml Data Annotator / Labeler Interview Questions
Quoted word for word from DataAnnotation interview reports.
“Write a story about a dancing green octopus, set on November 21st. Ensure the answer is not AI-generated.”
Read reports →“Questions about the correct syntax in python were asked, as well as javascript.”
Read reports →“lots of political questions to gauge your political spectrum”
Read reports →“There were some probability math questions too.”
Read reports →“Using the following three random topics, write a creative story.”
Read report →“Analyze what was wrong and what could be improved for a Python based coding query.”
Read report →“Which of the two AI prompt responses is superior and why? Provide a 2-3 sentence explanation.”
Read report →“Tell me about your education and why it fits this job.”
Read report →Formats, difficulty and experience
Across all 10 DataAnnotation interview reports.