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How much do data labeling analyst jobs pay per year?

As of May 28, 2026, the average yearly pay for data labeling analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is a Data Labeling Analyst job?

A Data Labeling Analyst is responsible for annotating, categorizing, and labeling data to help train machine learning models. They work with text, images, audio, or video data, ensuring accuracy and consistency according to predefined guidelines. This role requires attention to detail, a strong understanding of data patterns, and sometimes domain-specific knowledge to improve AI performance. Analysts often collaborate with data scientists and engineers to refine labeling strategies and enhance model training.

What are the key skills and qualifications needed to thrive in the Data Labeling Analyst position, and why are they important?

A Data Labeling Analyst requires strong attention to detail, excellent analytical abilities, and familiarity with data annotation and labeling processes, often supported by a bachelor's degree in a relevant field. Experience with annotation tools, basic knowledge of programming (such as Python), and familiarity with data management platforms are commonly sought after. Strong communication, time management, and the ability to work independently or as part of a distributed team are valuable soft skills. These skills ensure data accuracy and efficiency, which are critical for training reliable AI and machine learning models.

What are some common challenges faced by Data Labeling Analysts, and how can they be addressed?

One common challenge for Data Labeling Analysts is maintaining consistency and accuracy when labeling large volumes of complex data, as even minor errors can impact model performance. Frequent communication with project managers and data scientists can help clarify labeling guidelines and ensure alignment with project goals. Utilizing quality assurance processes, such as cross-checking work and leveraging feedback, also supports higher accuracy. Being adaptable and open to feedback helps analysts continuously improve and meet evolving project standards.
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Data Labeling Analyst jobs near you
Infographic showing various Data Labeling Analyst job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Italian Data Labeling Analyst(Speech & Voice)

Italian Data Labeling Analyst(Speech & Voice)

Welo Data

Manhattan, NY • On-site

Full-time

Posted 2 days ago

Job description

Job Summary:
Welo Data is looking for detail-oriented individuals to join their team as Data Labeling Analysts, supporting speech and voice AI systems. This role focuses on executing high-volume data labeling tasks and ensuring data integrity for AI training pipelines.
Responsibilities:
• Execute high-volume data labeling and annotation tasks across speech and voice datasets
• Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
• Work with audio and language data, including transcription, categorization, and tagging
• Maintain strong throughput while meeting quality expectations
• Escalate unclear or ambiguous cases appropriately
• Adapt to evolving guidelines and workflows as systems and requirements change
• Support baseline data production needs for AI training pipelines
• Contribute to team calibrations and quality alignment sessions
Qualifications:
Required:
• Native-level fluency in Croatian
• Strong written communication skills and language fundamentals
• 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
• Ability to follow detailed instructions and apply guidelines consistently
• High attention to detail and ability to maintain accuracy in repetitive tasks
• Comfort working in structured, process-driven environments
• Ability to manage time effectively and maintain steady output
• Willingness to ask questions and escalate when needed
Preferred:
• Basic familiarity with AI, speech technology, or language data is a plus
Company:
With 27+ years of experience, Welo Data is the human-centered infrastructure for globally effective AI. Founded in , the company is headquartered in , , with a team of 1001-5000 employees. The company is currently Late Stage.

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