Data Annotator Jobs
Updated October 9, 2026 · 1 verified employer
Latest Data Annotator Jobs
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How much do Data Annotator jobs pay?
Data Annotator positions pay a median of $59,280 per year, with the typical 25th‑to‑75th‑percentile range also at $59,280 – $59,280. Entry‑level roles have a median salary of $59,280. The average salary is $59,280, which is 92.2% below the national average of $760,351.
$59,280
25th %
$59,280
Median
$59,280
75th %
Is Data Annotator hiring growing?
Month-over-month hiring figures for Data Annotator jobs will appear once there is a full month of posting history.
Companies hiring for Data Annotator roles
100% remote · 100% full-time
Remote
100%
On-site
0%
Full-time
100%
Part-time
0%
A day in the life of a Data Annotator
- Review and label raw images, text, or audio according to project guidelines.
- Apply a predefined taxonomy to annotate data points for supervised learning.
- Perform quality checks and resolve ambiguities in annotations.
- Collaborate with project managers to refine annotation instructions.
- Document annotation decisions and flag inconsistent data.
Skills you need for Data Annotator jobs
- Attention to Detail
Data Annotator jobs: frequently asked questions
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What does a Data Annotator do?
A Data Annotator reviews raw data such as text, images, or audio and adds labels or tags that describe its content. These annotations create structured datasets that train and improve machine‑learning algorithms. The role requires following detailed guidelines to ensure consistency across large volumes of data.
What qualifications or tools are needed for a Data Annotator job?
Employers typically look for strong attention to detail and the ability to follow precise annotation instructions. Experience with annotation platforms like Labelbox or Scale AI is valuable, though many positions provide on‑the‑job training. A basic understanding of machine‑learning data requirements and good communication skills are also important.
Is Data Annotator a good career?
Demand for Data Annotators remains steady as AI projects expand, and the role offers fully remote, full‑time work. The position provides a clear entry point into the data‑focused technology sector.
How does a Data Annotator differ from a Data Analyst?
A Data Annotator focuses on labeling raw data to create training sets for AI models, while a Data Analyst interprets processed data to generate business insights. Annotation work relies on annotation tools and strict guidelines, whereas analysis uses statistical methods and visualization software. The environments also differ, with annotators often working remotely on repetitive tasks and analysts typically collaborating in office or hybrid settings.
Can you get a Data Annotator job with no experience?
Many Data Annotator positions provide training on specific annotation platforms, so lack of prior experience is not a barrier. Demonstrating meticulous attention to detail and the ability to follow instructions can be enough to secure an entry‑level role. Employers often prioritize candidates who can quickly adapt to project guidelines.