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Data Labeling Analyst Ii Jobs (NOW HIRING)

Welocalize, Inc.

Data Labeling Analyst

New York, NY · On-site

Annotate data accurately, ensuring it adheres to set guidelines. Quality Assurance and Analysis: * Conduct manual quality analysis of model results. * Recognize error patterns and report anomalies ...

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Data Labeling Analyst Ii information

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$82.6K

$136K

How much do data labeling analyst ii jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data labeling analyst ii 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 does a Data Labeling Analyst II do?

A Data Labeling Analyst II is responsible for accurately categorizing and annotating large datasets, which are often used to train machine learning models. This role involves reviewing data such as images, audio, text, or videos and applying predefined tags or labels according to specific guidelines. A Data Labeling Analyst II may also help improve labeling processes, provide feedback on data quality, and support junior analysts. Their work ensures that AI and data-driven technologies can learn effectively from high-quality, well-labeled data.

How does a Data Labeling Analyst II typically collaborate with data scientists and machine learning engineers during projects?

As a Data Labeling Analyst II, you will frequently work closely with data scientists and machine learning engineers to ensure datasets are accurately annotated for model training and validation. Collaboration often involves clarifying labeling guidelines, providing feedback on ambiguous cases, and adjusting annotation strategies based on project goals. Regular communication and review sessions help maintain consistency and high-quality data, which are vital for successful machine learning outcomes. This teamwork also offers opportunities to learn more about the end use of labeled data and to contribute ideas that improve overall data processes.

What are the key skills and qualifications needed to thrive as a Data Labeling Analyst II, and why are they important?

A Data Labeling Analyst II should possess strong attention to detail, familiarity with data annotation processes, and a background in computer science or a related field. Proficiency with data labeling tools such as Labelbox, Supervisely, or CVAT, as well as experience with database management systems, is typically required. Excellent communication, problem-solving abilities, and adaptability help analysts efficiently collaborate and manage evolving project requirements. These skills ensure the creation of high-quality labeled datasets, which are essential for training accurate machine learning models.
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Data Labeling Analyst Ii jobs near you
Infographic showing various Data Labeling Analyst Ii job openings in the United States as of June 2026, with employment types broken down into 69% Full Time, 8% Part Time, and 23% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Turkish Data Labeling Analyst(Speech & Voice )

Turkish Data Labeling Analyst(Speech & Voice )

Welo Data

Manhattan, NY • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Welo Data is looking for detail-oriented and reliable individuals to join their team as Data Labeling Analysts, supporting speech and voice AI systems. The role focuses on building datasets for AI systems through high-volume data labeling and annotation tasks, ensuring accuracy and consistency in working with audio and language data.
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.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.

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