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Data Annotation Research Jobs (NOW HIRING)

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... User Experience Research team. * Implement basic quality control measures and ensure the ...

Specter

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Role: Specter is hiring a data operations engineer to build our research data operation. This ... Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines ...

New

Turing

Client Director, Frontier Data - US

Palo Alto, CA

$255K - $325K/yr

Oversee the entire data lifecycle from client intake and annotation workflow design to delivery * Partner with product, research, and engineering teams to implement evaluation metrics (e.g., win rate ...

Mercor

Data Science Manager

New York, NY · Remote

$70 - $100/hr

Guide research and engineering teams on data science methodology , statistical inference , and ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and product teams to understand and formalize their requirements. * Identify and manage internal resources and ...

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

The Client's R&D Operations Organization is seeking a highly motivated and technically skilled Technical Program Manager (TPM) to lead and oversee data annotation programs that power our cutting-edge ...

Mercor

Chief Data Scientist

San Francisco, CA · Remote

$70 - $100/hr

Guide research and engineering teams on data science methodology , statistical inference , and ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Mercor

Data Scientist - AI/ML Expert

New York, NY · Remote

$70 - $100/hr

Guide research and engineering teams on data science methodology , statistical inference , and ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Mercor

AI Research Scientist - GenAI

New York, NY · Remote

$70 - $100/hr

Guide research and engineering teams to close knowledge gaps in AI and data science domains ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Mercor

Research And Development Scientist

New York, NY · Remote

$70 - $100/hr

Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Mercor

STEM Research Scientist - PhD

New York, NY · Remote

$70 - $100/hr

Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

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All JobsData Annotation Research Jobs

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
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Data Annotation Research jobs near you
Infographic showing various Data Annotation Research job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 3% Full Time, 71% Part Time, 3% Temporary, 17% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Quality Analyst

Data Quality Analyst

Welocalize, Inc.

San Francisco, CA • On-site

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

345th of 437 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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