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Remote Data Labeling Analyst Jobs (NOW HIRING)

Only Data Entry

Junior Data Entry Clerk (Remote)

Chicago, IL · Remote

$17.50 - $23.50/hr

As a Remote Data Entry Operator, you will play a pivotal role in ensuring that our data remains pristine and ready for analysis.Responsibilities:Accurately input, update, and maintain large volumes ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

... data labeling, annotation, and content evaluation * Participate in remote assignments or attend on ... analyzing resumes, or assessing responses. These tools assist our recruitment team but do not ...

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

As of Jun 5, 2026, the average yearly pay for remote data labeling 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 Remote Data Labeling Analyst, and why are they important?

To thrive as a Remote Data Labeling Analyst, you need strong attention to detail, analytical thinking, and basic data management skills, typically supported by a high school diploma or higher. Familiarity with annotation tools, data labeling platforms, and sometimes basic programming or spreadsheet software is required. Strong communication, time management, and the ability to work independently are crucial soft skills for excelling remotely. These abilities ensure high-quality, accurate data labeling that directly impacts the effectiveness of AI and machine learning systems.

What are some common challenges faced by Remote Data Labeling Analysts, and how can they be addressed?

Remote Data Labeling Analysts often encounter challenges such as maintaining focus during repetitive tasks, managing time effectively across multiple projects, and ensuring high accuracy in labeling complex data sets. To address these challenges, it is helpful to follow structured workflows, take regular breaks to reduce fatigue, and leverage collaboration tools to communicate with team members for clarification or feedback. Staying updated with labeling guidelines and participating in regular training sessions can also help improve both productivity and quality of work.

What does a Remote Data Labeling Analyst do?

A Remote Data Labeling Analyst is responsible for reviewing, tagging, and annotating data—such as images, videos, text, or audio—to help train machine learning models. Working remotely, they use specialized software to classify or categorize this data according to specific guidelines. Their work is crucial for improving the accuracy and performance of artificial intelligence systems, as well-labeled data enables the AI to learn and make better predictions. This role typically requires attention to detail, consistency, and the ability to follow complex instructions.

What is the difference between Remote Data Labeling Analyst vs Remote Data Annotator?

AspectRemote Data Labeling AnalystRemote Data Annotator
CredentialsBasic data labeling skills, familiarity with annotation toolsSimilar credentials, often entry-level
Work EnvironmentRemote, often part of a data teamRemote, typically individual tasks
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI training data preparation
Job FocusLabeling and categorizing data for machine learningAnnotating data with labels or tags

The Remote Data Labeling Analyst and Remote Data Annotator roles are similar, both involving data labeling tasks in a remote setting. The Analyst may have additional responsibilities like quality checks or data management, but both positions require similar skills and are used widely in AI and machine learning industries.

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Remote Data Labeling Analyst jobs near you

Remote Data Quality Analyst

Easy Recruiter

Centereach, NY • Remote

Full-time

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

Job description

About the job Remote Data Quality Analyst

Description

We are growing our enterprise data team of analysts, architects and engineers. This team is responsible for data governance, business intelligence, enterprise data architecture, data analytics, and ensuring that data is managed as a core corporate asset at OReilly. As a member of the enterprise data team, you will work collaboratively with engineering, product, security, data science, legal, and individuals throughout all areas of the business to ensure reliability, quality, and trustworthiness of data used for business decision making.

About The Job

As a Data Quality Analyst you will be responsible for helping OReilly ensure the reliability of our enterprise data. Data is one of our most important assets, and as a member of our data team you'll be responsible for helping us manage it. We are looking for a candidate who not only has the data analysis skills to successfully investigate, analyze and respond to day-to-day business issues, but also someone who has the ideas, experience and desire to help us build proactive solutions that will help us improve and grow the reliability, consistency and quality of our data platform as our company grows.

You Will

Investigate and manage questions and incidents related to enterprise data for root cause analysis.

  • Work with engineers to provide recommendations on solutions to existing data quality issues
  • Design, build and monitor key quality metrics dashboards, alerts and other monitoring tools
  • Implement proactive anomaly detection to identify potential data streams with errors; covering both the known and unknown
  • Collaborate on the design of a data quality framework
  • Work with data architects, product managers, engineers and business intelligence analysts to understand and define clear data definitions and conventions across the organization
  • Work with product managers and architects on product changes to help ensure an accurate understanding of the use and impact of data to ensure quality and reduce risk
  • Work directly with end users to define, understand and help solve questions and problems around data
  • Documentation of data classification, definitions and requirements across all data domains

About You

  • You have strong data analytics skills
  • You have proven experience doing data analysis at an enterprise level

Minimum Requirements

  • Bachelor's Degree required
  • 3+ years of experience doing similar work
  • Advanced knowledge in SQL
  • Previous experience with data analysis and data profiling
  • Experience working with a Data Governance Framework
  • Technical competency with cloud database technologies
  • A basic knowledge of Python

Bonus Points

  • Degree in statistics, mathematics, computer science, information management, or similar
  • Technical competency in ETL / ELT tools
  • Experience with digital analytics tools, like Google Analytics or Omniture
  • Hands-on experience with reporting technologies like Power BI
  • Familiarity with Data Governance tools like Collibra or Erwin
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