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Data Labelling Jobs (NOW HIRING)

About the role Our models are only as good as the data behind them. You'll own the labeling operation end to end -- the annotator team, the quality bar, the datasets themselves. This is a first-in ...

$90K - $125K/yr

About the role Our models are only as good as the data behind them. You'll own the labeling operation end to end -- the annotator team, the quality bar, the datasets themselves. This is a first-in ...

Healthcare Data Labeler / Data Annotator Location: Tampa, FL (5 days onsite) Duration: Long-term Contract Description and Skills: * 4-6 years of experience in data labeling/annotation. * Perform ...

The Labelling & Data Automation team plays a critical role in Waabi's training pipeline. We are one of the first steps in the process of training machine learning models and are responsible for ...

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Data Labelling information

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$46K

$165K

$243.5K

How much do data labelling jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.
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Infographic showing various Data Labelling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Operational Data Analyst

Oklahoma City, OK • On-site

$60K - $75K/yr

Full-time

Re-posted 11 days ago


Job description

Job Description


The Operations Data Analyst is responsible for data analysis requests and the support of our internal Operations Teams. Responsibilities include research into processing metrics and exception reduction as well as quality control and cost-reduction insight. This team works alongside Operations, Development, and External Client Teams to define and implement improvements for the day-to-day processing of volume.


Duties and Responsibilities

  • Provide long-term reporting, team metrics and quality control insight using tools such as Microsoft SQL Server, Sisense, Excel, Python, and more
  • Research and develop suggested improvements for production processing efficiency
  • Create, test, and maintain SQL stored procedures alongside a Unit Test environment
  • Work with proprietary software to manage internal document extraction methods through building, testing, and deployment pipelines
  • Perform dataset collection for creation of new machine learning processes
  • Perform data labelling and dataset refinement to fine-tune current and future machine learning methods
  • Manage and resolve data extraction inconsistencies per client standard
  • Other duties and responsibilities as assigned


Qualifications

  • 1-3 years SQL and Python
  • Data Analytic/Mining skills required
  • Experience with Jira or similar ticket tools preferred.
  • Experience with version control (GIT, CVS)
  • Experience with query performance tuning preferred
  • Experience troubleshooting in a live production environment preferred
  • Experience with large datasets preferred
  • Experience with high volume and fast turnaround preferred
  • Proficiency in MS Office Suite
  • Understanding of Healthcare claims and payments revenue cycle strongly desired
  • Problem-solving skills
  • Excellent verbal and written communication skills
  • Excellent organizational skills and attention to detail
  • Able to multitask, prioritize, and manage time effectively
  • Attention to detail


Education/Experience

A bachelor's degree in a technical field is not required, but preferred. More than anything, RMS is looking for people who are passionate about technology who want to develop the skills to solve hard and important problems.


Environmental Conditions

Indoor climate-controlled environment. Moderate to quiet noise level


Physical requirements

While performing the duties of this Job, the employee is regularly required to communicate verbally and in the written form. The employee is physically required to utilize a laptop and other electronic devices effectively. The employee must lift and/or move up to 20 pounds (laptop computer, bag, and accessories). Specific vision abilities required by this job include close vision and distance vision.


All applicants are subject to a drug screen and background check per company policies