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

DataAnnotation

M&A Associate - 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

Financial Planner - 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

Financial Planner - 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 ...

DataAnnotation

M&A Associate - 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 Annotation Analyst JobsRemote Data Annotation Analyst JobsRemote Data Annotation Analyst Jobs in Reno, NV

Remote Data Annotation Analyst information

See Reno, NV salary details

$33.9K

$82.4K

$135.6K

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

As of Jul 11, 2026, the average yearly pay for remote data annotation 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.

How does a Remote Data Annotation Analyst typically collaborate with team members and ensure consistent labeling standards?

As a Remote Data Annotation Analyst, you’ll frequently work within a distributed team, using collaboration tools such as Slack, project management platforms, and shared annotation guidelines. Regular virtual meetings and feedback sessions help ensure everyone applies labeling standards consistently and resolves ambiguities. It’s common to review peer annotations and participate in quality assurance checks, promoting a culture of accuracy and continuous improvement. Clear communication and attention to detail are essential for maintaining high-quality annotated datasets across the team.

What are Remote Data Annotation Analysts?

Remote Data Annotation Analysts are professionals who label, categorize, or tag data—such as images, text, audio, or video—from a remote location. Their work helps train machine learning algorithms by providing structured datasets that computers can learn from. These analysts use specialized tools to identify relevant features in raw data, ensuring accuracy and consistency. The role often requires attention to detail, basic technical skills, and the ability to follow specific guidelines or instructions. This position is commonly found in industries like artificial intelligence, autonomous vehicles, and natural language processing.

What is the difference between Remote Data Annotation Analyst vs Remote Data Labeler?

AspectRemote Data Annotation AnalystRemote Data Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentHome-based, flexible hoursHome-based, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnalyzing and verifying labeled data, quality controlLabeling data, annotating images, text, or audio

The main difference is that Remote Data Annotation Analysts focus on verifying and ensuring the quality of labeled data, often involving analysis and review, while Remote Data Labelers primarily perform the task of labeling or annotating raw data. Both roles are essential in AI development and share similar work environments and skill requirements, but their specific responsibilities differ in scope and focus.

What are the key skills and qualifications needed to thrive as a Remote Data Annotation Analyst, and why are they important?

To thrive as a Remote Data Annotation Analyst, you need strong attention to detail, analytical thinking, and a high school diploma or equivalent, with many roles preferring experience in data-related tasks. Familiarity with data annotation platforms (like Labelbox or AWS SageMaker Ground Truth) and basic understanding of data management tools are typically required. Excellent time management, self-motivation, and clear communication help analysts manage remote workloads and collaborate effectively with distributed teams. These skills ensure accurate, high-quality annotated data essential for training and validating machine learning models.
What are popular job titles related to Remote Data Annotation Analyst jobs in Reno, NV? For Remote Data Annotation Analyst jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Remote Data Annotation Analyst jobs in Reno, NV look for? The top searched job categories for Remote Data Annotation Analyst jobs in Reno, NV are:
Remote Data Annotation Analyst jobs near you

Work From Home - Bilingual Client Services Representative

AO Garcia Agency

Carson City, NV • Remote

$15.25 - $19/hr

Other

Posted 15 days ago

Job description

Are you bilingual and looking for an opportunity to grow your career at your own pace?

We are looking for goal-oriented individuals with leadership potential to join a
rapidly growing company.

Preferred Qualifications:
Bilingual (Spanish and English)
Excellent communication skills Leadership capabilities
Self-starter
Positive attitude
Growth mindset

We Offer:
100% remote positions
Uncapped earning potential
Opportunity to enter into leadership

*All interviews will be conducted via Zoom video conferencing
(Global Elite Empire Consultants is a third-party recruiter, not an insurance agency)
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.
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