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Remote Data Labeling Analyst Jobs (NOW HIRING)

Landpoint

Remote Data Analyst

Fremont, CA · Remote

These essential skills enable analysts to effectively work with data, collaborate with remote teams, and provide valuable insights that drive business growth. Skills; Analytical and problem-solving ...

Jobsultant Solutions

Remote Data Analyst

Dallas, TX · Remote

Work Environment: * 100% remote - must work in CST * 8am-5pm (9 hour day with one hour lunch break ... Own Brand (private label) reporting, recapping, tracking, and analysis, including ad-hoc analysis ...

Recruit Monitor

Remote Data Analyst

San Jose, CA · Remote

You will design and develop data & analytics solutions using cutting-edge tools to improve data warehousing, financial reporting, reserve analytics, and various automation efforts. This position ...

Recruit Monitor

Remote Data Analyst

Long Beach, CA · Remote

You will design and develop data & analytics solutions using cutting-edge tools to improve data warehousing, financial reporting, reserve analytics, and various automation efforts. This position ...

Total AI

Be Seen First

Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

Total AI

Be Seen First

Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

Easy Recruiter

Remote Data Analyst

Chicago, IL · Remote

As a Data Analyst, you will be responsible assisting with resolution of consumer/commercial card and loan bank wide issues. You will be identifying impacted accounts based on requirements. As a Data ...

Total AI

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Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

TSMG

AI/ML Data Contributor

Des Moines, IA · Remote

... data labeling, annotation, and content evaluation * Participate in remote assignments or attend on ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

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Remote Data Labeling Analyst information

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$34K

$82.6K

$136K

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

As of Aug 7, 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?

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.

More about Remote Data Labeling Analyst jobs
What cities are hiring for Remote Data Labeling Analyst jobs? Cities with the most Remote Data Labeling Analyst job openings:
What are the most commonly searched types of Data Labeling Analyst jobs? The most popular types of Data Labeling Analyst jobs are:
What states have the most Remote Data Labeling Analyst jobs? States with the most job openings for Remote Data Labeling Analyst jobs include:
What job categories do people searching Remote Data Labeling Analyst jobs look for? The top searched job categories for Remote Data Labeling Analyst jobs are:
Remote Data Labeling Analyst jobs near you
Infographic showing various Remote Data Labeling Analyst job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Remote Data Analyst

Landpoint

Fremont, CA • Remote

Full-time

Re-posted 9 days ago

Job description

What is data analyst ?

A data analyst is a professional who collects, cleans, and analyzes data to answer questions or solve problems. They work in many industries, including business, finance, science, medicine, and government

To excel as a remote data analyst, professionals must possess a combination of technical skills, soft skills, and industry-specific expertise. These essential skills enable analysts to effectively work with data, collaborate with remote teams, and provide valuable insights that drive business growth.

Skills;

Analytical and problem-solving skills

Knowledge of statistics and mathematics

Experience with spreadsheets

Experience with statistical languages

Experience with scripting languages

Knowledge of database management systems

Data visualization skills

Data Analyst Job Description: Key Responsibilities

Remote data analysts play a crucial role in driving business growth and decision-making by transforming raw data into actionable insights. Their key responsibilities include:

Collecting and interpreting data from various sources: Data analysts are responsible for gathering data from multiple sources, such as databases, APIs, and spreadsheets. They then interpret this data, identifying patterns and trends that can provide valuable insights for the business.

Analyzing data to identify trends and patterns: Once the data has been collected and interpreted, data analysts use various statistical methods and tools to analyze it. By identifying trends and patterns, they can provide insights that help businesses make data-driven decisions.

Creating reports and visualizations to present findings: Data analysts use data visualization tools like Tableau and Power BI to create clear and engaging reports that effectively communicate their findings to stakeholders. These visualizations help businesses understand complex data and make informed decisions.

Collaborating with cross-functional teams to support business objectives: Data analysts work closely with various teams within the organization, such as marketing, sales, and product development. By collaborating with these teams, they can provide data-driven insights that help support the company's overall business objectives.

Ensuring data accuracy and compliance with relevant regulations: Data analysts must ensure that the data they collect and analyze is accurate and reliable. They must also comply with any relevant regulations, such as data privacy laws, to protect the organization from potential legal issues.

Technical Skills

Data manipulation and analysis tools: Proficiency in tools like Excel, SQL, Python, and R is crucial for data analysts to efficiently collect, clean, and analyze data from various sources.

Data visualization tools: Mastery of visualization tools such as Tableau and Power BI helps analysts create impactful visual representations of their findings, making it easier for stakeholders to understand complex data.

Knowledge of statistical methods and machine learning algorithms: A deep understanding of statistical methods and machine learning algorithms allows data analysts to identify trends and patterns, providing valuable insights for decision-making.

Soft Skills

Effective communication and collaboration: Remote data analysts must be able to clearly and concisely communicate their findings and collaborate with cross-functional teams to support business objectives.

Attention to detail and problem-solving abilities: A keen eye for detail and strong problem-solving skills are essential for identifying data anomalies and ensuring data accuracy.

Time management and organization: Remote work requires excellent time management and organizational skills to stay on track and meet deadlines.

Adaptability and self-learning capabilities: As technology and industry trends evolve, remote data analysts must be adaptable and committed to continuous learning to stay ahead of the curve.

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