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Remote Data Labeling Analyst Jobs in Philadelphia, PA

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

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

TSMG

AI/ML Data Contributor

Philadelphia, PA · 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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All JobsData Labeling Analyst JobsRemote Data Labeling Analyst JobsRemote Data Labeling Analyst Jobs in Philadelphia, PA

Remote Data Labeling Analyst information

See Philadelphia, PA salary details

$34.3K

$83.4K

$137.2K

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

As of Aug 21, 2026, the average yearly pay for remote data labeling analyst in Philadelphia, PA is $83,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,100.00 and $97,900.00 per year, depending on experience, location, and employer.

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 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 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.

What are the most commonly searched types of Data Labeling Analyst jobs in Philadelphia, PA?

The most popular types of Data Labeling Analyst jobs in Philadelphia, PA are:

What are popular job titles related to Remote Data Labeling Analyst jobs in Philadelphia, PA?

For Remote Data Labeling Analyst jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Remote Data Labeling Analyst jobs in Philadelphia, PA look for?

The top searched job categories for Remote Data Labeling Analyst jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Remote Data Labeling Analyst jobs?

Cities near Philadelphia, PA with the most Remote Data Labeling Analyst job openings:

Remote Data Labeling Analyst jobs near you
Infographic showing various Remote Data Labeling Analyst job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $83,391 per year, or $40.1 per hour.

AI/ML Data Contributor

TSMG

Philadelphia, PA • Remote

Full-time

Re-posted 24 days ago

Job description

Project Overview
We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing.

Projects may vary in scope and format, offering both remote and in-person opportunities (such as device or VR testing). This is a flexible, task-based role with the opportunity to participate in multiple projects over time.

Responsibilities
  • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation
  • Participate in remote assignments or attend on-site sessions when required
  • Follow project guidelines and ensure high-quality task completion
  • Provide feedback and input during testing activities
  • Complete tasks within given timelines
Requirements
  • Must be based in the United States
  • Strong attention to detail and ability to follow instructions
  • Basic computer skills and familiarity with digital tools
  • Reliable internet connection and access to a computer or smartphone
  • Availability to participate in task-based work (schedule may vary)
Nice to Have
  • Previous experience in data annotation, QA, or testing
  • Interest in AI, machine learning, or emerging technologies
What We Offer
  • Paid, flexible task-based work
  • Opportunity to work on innovative AI/ML projects
  • Exposure to cutting-edge technologies (including device and VR testing)
  • Potential for ongoing project participation

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.