Data Annotation Specialist resume skills and keywords
In 30 Data Annotation Specialist job postings from 20 employers analysed on October 23, 2026, the most requested skills are Attention to detail (57 %), Data Annotation (57 %), Machine learning (33 %), Labeling (30 %) and Communication (30 %). Of the top 31 skills, 27 are hard skills, tools or certifications and 4 are soft skills.
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Top 31 skills in Data Annotation Specialist job postings
| Skill | Share of postings | Type |
|---|---|---|
| Attention to detail | 57 % | Soft skill |
| Data Annotation | 57 % | Hard skill |
| Machine learning | 33 % | Hard skill |
| Labeling | 30 % | Hard skill |
| Communication | 30 % | Soft skill |
| Quality assurance | 27 % | Hard skill |
| PLC | 17 % | Tool |
| AI Technologies | 17 % | Hard skill |
| Segmentation | 17 % | Hard skill |
| Calibration | 17 % | Hard skill |
| Continuous improvement | 17 % | Hard skill |
| Artificial Intelligence | 13 % | Hard skill |
| Python | 13 % | Tool |
| Localization | 13 % | Hard skill |
| User Experience | 13 % | Hard skill |
| Computer vision | 13 % | Hard skill |
| Natural language processing | 13 % | Hard skill |
| Data Analysis | 13 % | Hard skill |
| Machine Learning Models | 13 % | Hard skill |
| Analytical skills | 13 % | Soft skill |
| LLMs | 13 % | Tool |
| Microsoft Excel | 10 % | Tool |
| Google Workspace | 10 % | Tool |
| Model evaluation | 10 % | Hard skill |
| Intrusion Detection Systems | 10 % | Hard skill |
| CAD | 10 % | Hard skill |
| And Labeling | 10 % | Hard skill |
| Flexibility | 10 % | Soft skill |
| Translation | 10 % | Hard skill |
| SQL | 10 % | Tool |
| Hours of service | 10 % | Hard skill |
Hard skills vs soft skills vs tools and certifications
Hard skills (21)
- Data Annotation 57 %
- Machine learning 33 %
- Labeling 30 %
- Quality assurance 27 %
- AI Technologies 17 %
- Segmentation 17 %
- Calibration 17 %
- Continuous improvement 17 %
- Artificial Intelligence 13 %
- Localization 13 %
- User Experience 13 %
- Computer vision 13 %
- Natural language processing 13 %
- Data Analysis 13 %
- Machine Learning Models 13 %
- Model evaluation 10 %
- Intrusion Detection Systems 10 %
- CAD 10 %
- And Labeling 10 %
- Translation 10 %
- Hours of service 10 %
Soft skills (4)
- Attention to detail 57 %
- Communication 30 %
- Analytical skills 13 %
- Flexibility 10 %
Tools and software (6)
- PLC 17 %
- Python 13 %
- LLMs 13 %
- Microsoft Excel 10 %
- Google Workspace 10 %
- SQL 10 %
Keyword phrases recruiters use
Multi-word phrases that recur across these data annotation specialist postings, with the share of postings that use each one.
How to use this on your resume
Treat the table as a checklist, not a script. Put the skills you genuinely have in your skills section, using the same wording as the posting, and back the top ones with a bullet that shows the result.
Each job posting differs from the average, so compare your resume with the actual ad: paste it into the resume keyword scanner to see which terms you already have and which are missing. The ATS keywords guide explains where to place them so applicant tracking systems read them.
Skip any skill you cannot talk about in an interview; a keyword that falls apart under one question costs more than it gains. For a full layout with these skills in context, see the Data Annotation Specialist resume example. Then prepare for the Data Annotation Specialist interview questions that test them.
Build a data annotation specialist resume with these skills
Start in the editor, tailor your bullets to the job you want and download an ATS-friendly resume.