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Data Labeling Analyst information

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$82.6K

$136K

How much do data labeling analyst jobs pay per year?

As of Jun 18, 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 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.

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 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.

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Data Labeling Analyst jobs near you
Italian Data Labeling Analyst(Speech & Voice)

Italian Data Labeling Analyst(Speech & Voice)

Welocalize

Seattle, WA

$26 - $28/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Be an early applicant

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

335th of 428 rated business services

Job description

Overview

Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.

This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.

While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.

We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.

Project Details
  • Job Title: Data Labeling Analyst
  • Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $26 - $28/hour

Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, or Burlingame. Please only apply if you meet this location requirement.

What You'll Do
  • 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
What We're Looking For
  • 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
  • Basic familiarity with AI, speech technology, or language data is a plus
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)

Onsite Perks (where applicable):
Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location

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