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Internship Data Annotation Analyst Jobs (NOW HIRING)

Welocalize, Inc.

Data Quality Analyst

New York, NY

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Quality Assurance and Analysis: * Conduct manual quality analysis of model results. * Recognize ...

JPMorganChase

Data Domain Architect Lead

Wilmington, DE · On-site

Responsibilities : • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in ...

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Internship Data Annotation Analyst information

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How much do internship data annotation analyst jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for internship data annotation analyst in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

How hard is it to get hired by data annotation?

Getting hired as a data annotation analyst generally requires attention to detail, basic computer skills, and familiarity with annotation tools or platforms. Many positions are entry-level and may not require extensive experience, making the role accessible to beginners, though some jobs may prefer knowledge of specific data types or industry standards.

What is a data annotation internship?

A data annotation internship is a temporary position where interns assist in labeling and categorizing data, such as images, text, or videos, to help train machine learning models. Interns typically use annotation tools and develop skills in data quality and accuracy under supervision. This role provides practical experience in data preparation and AI development processes.

What does a data annotation analyst do?

A data annotation analyst is responsible for labeling and categorizing data, such as images, text, or videos, to prepare it for machine learning models. They use tools and follow guidelines to ensure data accuracy and consistency, which is essential for training effective AI systems.

What is the difference between Internship Data Annotation Analyst vs Data Labeling Specialist?

AspectInternship Data Annotation AnalystData Labeling Specialist
CredentialsTypically pursuing or recent graduate in related fieldRelevant certifications or experience preferred
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation companies
Industry UsageCommon in AI, machine learning, and tech industriesUsed across AI, autonomous vehicles, and healthcare sectors

The Internship Data Annotation Analyst is usually an entry-level role for students or recent graduates gaining experience in data annotation. In contrast, Data Labeling Specialists are more experienced professionals focused on accurately labeling data for AI models. Both roles are essential in AI development, but the internship provides learning opportunities, while the specialist role involves more independent work and expertise.

Does data annotation actually pay?

Data annotation analysts are typically paid for their work, with compensation varying based on the project, platform, or employer. Many companies offer hourly rates or per-task payments, and some roles may require specific skills or tools. Payment is generally reliable for those working in paid annotation jobs, especially with established platforms or companies.
What cities are hiring for Internship Data Annotation Analyst jobs? Cities with the most Internship Data Annotation Analyst job openings:
What are the most commonly searched types of Data Annotation Analyst jobs? The most popular types of Data Annotation Analyst jobs are:
What states have the most Internship Data Annotation Analyst jobs? States with the most job openings for Internship Data Annotation Analyst jobs include:
Internship Data Annotation Analyst jobs near you
Data Labeling Analyst

Data Labeling Analyst

Welocalize, Inc.

San Diego, CA

Full-time

Posted 13 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

361st of 451 rated business services

Job description

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Job Responsibilities:

The ideal candidate will have a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. They will play a pivotal role in updating our machine learning models and ensuring their efficacy.

MAIN TASKS & RESPONSIBILITIES

Machine Learning Model Updates:

  • Update training and test model databases with new or amended synthetic textual and image data.
  • Modify and refine machine learning data creation, annotation, and rating guidelines.

Model Training and Evaluation:

  • Initiate model training processes using internal tools and command-line interfaces.
  • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.

Data Management and Annotation:

  • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
  • Handle data efficiently, ensuring its integrity throughout the workflow.
  • Engage in data relevance tasks, ensuring data sets are aligned with project goals.
  • 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 for further investigation.
  • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
  • Implement basic quality control measures and ensure the reliability of processed data.
  • Utilize intermediate data analysis techniques to extract insights and inform decision-making.
  • Arbitrate discrepancies effectively, ensuring consistent data quality.

Linguistic and NLP Tasks:

  • Apply basic knowledge of natural language processing and linguistics to data processing tasks.
  • Ensure linguistic accuracy in all processed and annotated data.

REQUIREMENTS

Preferred Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills

Skills & Knowledge:

  • Familiarity with command-line tools and interfaces.
  • Strong analytical skills with the ability to identify patterns and anomalies.

Additional Information:

This role primarily focuses on English US data sets; however, familiarity with translation or multi-lingual data sets can be a plus for future projects.

Additional Job Details:

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