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Remote Data Labeling Analyst Jobs in Reno, NV (NOW HIRING)

Employers

Tax Analyst

Reno, NV · Remote

Tax Analyst |100% Remote (WFH) Opportunity General Summary The successful candidate will become a ... Gather, analyze, and synthesize data from diverse systems. Organize and reference schedules and ...

Sierra Nevada Corporation

Pricing Analyst III

Sparks, NV · On-site +1

$85K - $117K/yr

If you have a keen eye for the big picture, excellent technical data analysis skills, and enjoy ... Work in an office environment with the potential for hybrid or remote work settings. At Sierra ...

DataAnnotation

Treasury Analyst - AI Trainer

Reno, NV · Remote

$50 - $60/hr

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

DataAnnotation

Treasury Analyst - AI Trainer

Sparks, NV · Remote

$50 - $60/hr

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

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All JobsData Labeling Analyst JobsRemote Data Labeling Analyst JobsRemote Data Labeling Analyst Jobs in Reno, NV

Remote Data Labeling Analyst information

See Reno, NV salary details

$33.9K

$82.4K

$135.6K

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

As of Jul 8, 2026, the average yearly pay for remote data labeling analyst in Reno, NV is $82,398.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,300.00 and $96,700.00 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.

What are popular job titles related to Remote Data Labeling Analyst jobs in Reno, NV? For Remote Data Labeling Analyst jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Remote Data Labeling Analyst jobs in Reno, NV look for? The top searched job categories for Remote Data Labeling Analyst jobs in Reno, NV are:
What cities near Reno, NV are hiring for Remote Data Labeling Analyst jobs? Cities near Reno, NV with the most Remote Data Labeling Analyst job openings:
Remote Data Labeling Analyst jobs near you
AI Data Collector - Computer Vision (Remote/Contract)

AI Data Collector - Computer Vision (Remote/Contract)

micro1 AI

Reno, NV • Remote

$13/hr

Part-time

Posted 12 days ago

Job description

Job Title: Data-Video Generalist


Job Type: Contractor


Location: Remote - experts based in Alabama, Arkansas, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, Montana, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Virginia, West Virginia, and Wisconsin.


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Capture precise motion data using your smartphone during specified physical tasks.
  2. Supported devices include the iPhone 12 and later, Google Pixel 6 and later, and Samsung Galaxy S21 and later.
  3. Record synchronized video footage to validate and enhance the integrity of collected sensor data.
  4. Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards.
  5. Consistently contribute a minimum of 10 hours of approved video data per week throughout the project duration.
  6. Communicate effectively with the team to clarify guidelines and provide feedback on data collection processes.
  7. Ensure timely and reliable delivery of data outputs in accordance with project milestones.
  8. Participate in required device compatibility checks and a custom AI-enabled interview process.


Required Skills and Qualifications:

  1. Access to a head strap to be able to record both hands within 48 hours of the start date.
  2. Demonstrated adherence to standardized protocols and rigorous technical instructions.
  3. Proven ability to manage and deliver reliable output in a fast-paced, data-driven environment.
  4. Strong written and verbal communication skills; ability to document work and collaborate remotely.
  5. Experience with mobile devices and a high level of digital literacy.
  6. Physical capability to perform repetitive movement tasks safely and accurately.
  7. Access to a compatible smartphone for high-fidelity sensor and video data collection.
  8. Eligibility to work in designated U.S. states.
  9. Note: Applications submitted with a Gmail address are strongly preferred for seamless tool integration.


Compensation Structure

Compensation is output-based; experts are paid per recorded video that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow.


Start Timeline & Availability

We typically fill roles within 48 hours, so we’re looking for teammates who are ready to jump in. If selected, we’d love for you to start your first task as soon as you move forward with your application. The expectation is to begin within ~24 hours of completing onboarding.


Equipment Requirements

Mobile:

Tasks for this project must be performed from a mobile device (smartphone). Experts will record their workflow directly from the mobile device while completing tasks.


Head Strap / Wearable: Tasks for this project must be performed using a head-mounted camera (head strap setup). Experts will record first-person video of physical tasks. The required head strap and any accompanying equipment specifications will be shared during onboarding.

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