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Flexible Data Annotation Analyst Jobs (NOW HIRING)

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into ... Flexible PTO to fully recharge * 18 paid vacation days in the U.S. plus federal holidays * Annual ...

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 ...

Welocalize, Inc.

OR

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 ...

Welocalize, Inc.

OR

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 ...

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How much do flexible data annotation analyst jobs pay per year?

As of May 31, 2026, the average yearly pay for flexible data annotation 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 the key skills and qualifications needed to thrive as a Flexible Data Annotation Analyst, and why are they important?

To thrive as a Flexible Data Annotation Analyst, you need keen attention to detail, analytical thinking, and a basic understanding of data labeling processes, often supported by a high school diploma or relevant experience. Familiarity with annotation tools such as Labelbox, Prodigy, or similar platforms, as well as basic proficiency in spreadsheet software, is typically required. Strong time management, adaptability, and clear communication skills help you deliver accurate results and work effectively with remote teams. These abilities ensure high-quality, consistent data labeling that is critical for training reliable machine learning models.

How does a Flexible Data Annotation Analyst typically collaborate with other teams to ensure data quality?

As a Flexible Data Annotation Analyst, you will frequently interact with data scientists, machine learning engineers, and project managers to clarify annotation guidelines and resolve ambiguities in the data. Collaboration often involves participating in virtual meetings, providing feedback on annotation tools, and reporting inconsistencies or uncertainties encountered during the labeling process. This teamwork ensures that annotated datasets meet project standards and contribute to high-quality machine learning outcomes. Regular communication and openness to feedback are key to success in this collaborative environment.

What is a Flexible Data Annotation Analyst?

A Flexible Data Annotation Analyst is a professional responsible for labeling, categorizing, and tagging data—such as text, images, audio, or video—to prepare it for use in machine learning and artificial intelligence projects. The 'flexible' aspect typically means the role allows for remote work, adjustable hours, or project-based assignments. Analysts use specific tools and follow detailed guidelines to ensure data quality and consistency. This role is crucial for training accurate AI models, as well-annotated data helps improve the performance of automated systems.
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Flexible Data Annotation Analyst jobs near you
Generative AI Data Analyst - USA (Remote)

Generative AI Data Analyst - USA (Remote)

Welo Data

Charleston, WV • Remote

$27.38/hr

Full-time

Posted 24 days ago

Job description

OVERVIEW

We are seeking a Generative AI Analyst to support a high-impact machine learning project. This role focuses on creating high-quality prompts and responses across diverse topics and leading labeling initiatives with internal and external partners. The ideal candidate is a strong communicator with native-level U.S. English, experienced in working with data and comfortable training teams on best practices for LLM development. This position is fully remote and suited for someone motivated to work with cutting-edge AI technologies.

Project Details

Job Title: Generative AI Analyst
Location: Remote
Hours: 40 hours weekly
Language: English (US)
Start date: April 2026
Employment Type: Full-time W-2 employee with benefits – 5 days a week
Pay rate: $27.38/hour
If you reside in California, please apply to the California-specific posting for the applicable rate

Must have valid work authorization in the US (Welo Data does not sponsor VISAs at this time).

Key Responsibilities
  • Creatively writing prompts and responses to a variety of diverse topics
  • Perform LLM annotation and evaluation tasks (ranking, scoring, labeling, tagging)
  • Evaluate model outputs for accuracy, relevance, and instruction-following
  • Identify and document issues such as hallucinations and inconsistencies
  • Participating in and/or supporting labeling workflows, including hands-on annotation and collaboration with internal or external teams
  • Training teams on best practices for creating Large Language Models/Data sets
Requirements
  • Hands-on experience performing data annotation or evaluation tasks (e.g., labeling, ranking, scoring, or tagging LLM outputs)
  • Native or near-native English with excellent writing skills
  • Strong attention to detail and ability to follow guidelines consistently
  • Self-driven, motivated and enthusiastic to work on state-of-art machine learning tools
  • 4 year Accredited College degree or equivalent experience

Ways to stand out from the crowd:

  • College Degree or experience in Linguistics, English Literature, Creative Writing, Journalism, and domain knowledge (Law/Medical/Math/Coding/etc.)
  • Experience working in annotation platforms or structured labeling environments is a plus
  • Deep understanding of Large Language Models/RLHF
  • Experience in labeling/tagging of frames/tasks/prompts to prepare for DNN
  • QA/testing experience

Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.