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Hourly Remote Data Labeling information

What are the key skills and qualifications needed to thrive as an hourly remote data labeler?

To thrive as an Hourly Remote Data Labeler, you need strong attention to detail, basic computer literacy, and the ability to follow specific guidelines, often with a high school diploma or equivalent. Familiarity with data annotation tools and platforms such as Labelbox, Prodigy, or internal company systems is typically required. Reliability, time management, and effective written communication are crucial soft skills for meeting deadlines and maintaining quality in a remote setting. These skills and qualities are important to ensure accurate, consistent data labeling that directly impacts the performance of AI and machine learning models.

What is the difference between Hourly Remote Data Labeling vs Data Annotation Specialist?

AspectHourly Remote Data LabelingData Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with some industry-specific knowledge
Work EnvironmentRemote, flexible hoursRemote, often project-based or ongoing
Industry UsageCommon in AI/ML developmentUsed across tech, healthcare, automotive sectors
Search IntentLooking for remote data labeling jobsSearching for data annotation roles

Both roles involve labeling or annotating data for machine learning models, often remotely. The main difference lies in terminology and specific industry usage, but they share similar credentials and work environments.

What is hourly remote data labeling?

Hourly remote data labeling is a job where individuals work from home to tag, categorize, or annotate data (such as images, videos, text, or audio) for machine learning and artificial intelligence projects. Workers are typically paid by the hour and use online platforms to complete labeling tasks assigned by companies or research organizations. This work is crucial because AI models need large volumes of accurately labeled data to learn and function properly. The job usually requires attention to detail and may involve following specific guidelines to ensure data quality.

What are some common challenges faced by hourly remote data labelers, and how can they be managed?

Hourly remote data labeling professionals often encounter challenges such as maintaining consistent accuracy, managing repetitive tasks, and staying self-motivated while working independently. To manage these challenges, it's important to set up a dedicated workspace, take regular breaks to reduce fatigue, and follow established labeling guidelines closely. Frequent communication with team leads and participating in quality feedback sessions can also help ensure your work meets project standards and fosters professional growth.
What are the most commonly searched types of Remote Data Labeling jobs in New York? The most popular types of Remote Data Labeling jobs in New York are:
What are popular job titles related to Hourly Remote Data Labeling jobs in New York? For Hourly Remote Data Labeling jobs in New York, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Data Labeling jobs in New York look for? The top searched job categories for Hourly Remote Data Labeling jobs in New York are:
What cities in New York are hiring for Hourly Remote Data Labeling jobs? Cities in New York with the most Hourly Remote Data Labeling job openings:
Hourly Remote Data Labeling jobs near you

Quantitative Analyst - Fully Remote | Upto $90/hr

Mercor

New York, NY • Remote

$90/hr

Full-time

Posted 5 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Science & Quantitative Analysis Expert
Type: Contract
Compensation: $60–$90/hour
Location: Remote
Commitment: 35 hours/week

Role Responsibilities

  • Design complex analysis tasks simulating real research work, including data cleaning, statistical analysis, and interpretation.
  • Author clear, reproducible reference analyses in Jupyter Notebooks or Google Colab.
  • Build tasks for fair comparison between analytical approaches, backed by spot checks and recommendations.
  • Evaluate how models handle tasks and verify the accuracy of their statistics and conclusions.
  • Collaborate with researchers to ensure consistent and accurate evaluations.

Qualifications

Must-Have

  • MSc or PhD in statistics, data science, or a quantitative STEM field, or equivalent experience.
  • 1+ years in a research, research-engineering, or heavy data-analysis role.
  • Proficiency in Python (pandas, NumPy) and Git.
  • Strong data-analysis skills: data cleaning, statistical correlation, hypothesis testing, and result interpretation.
  • Ability to communicate analytical findings effectively in writing.

Preferred

  • Experience in AI training, model evaluation, or benchmark/task authoring.
  • High attention to detail and creativity in task design.

Compensation & Legal

  • Hourly contractor, Paid weekly via Stripe Connect

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.