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Remote Data Annotation Jobs in Byram, CT (NOW HIRING)

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Remote Commitment: 15 hours/week Role Responsibilities * Review and annotate U.S. court opinions ... Prior experience in legal data annotation or AI/ML projects . * Familiarity with CourtListener

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Prior experience with RLHF, model evaluation, or data annotation work . * Experience writing or ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Prior experience with RLHF, model evaluation, or data annotation work * Experience writing or ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Experience with RLHF, model evaluation, or data annotation work * Experience writing or editing ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Prior experience with RLHF, model evaluation, or data annotation work . * Experience writing or ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Experience with RLHF, model evaluation, or data annotation work * Experience writing or editing ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Prior experience with RLHF, model evaluation, or data annotation work . * Experience writing or ...

Remote Role Responsibilities * Conduct fact-checking using trusted public sources and external ... Prior experience with RLHF, model evaluation, or data annotation work * Experience writing or ...

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Remote Data Annotation information

What are the key skills and qualifications needed to thrive in the Remote Data Annotation position, and why are they important?

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

How to make $1000 a week remote?

Remote data annotation jobs typically pay per task or hour, with earnings varying based on experience, task complexity, and volume. To reach $1000 weekly, workers often need to complete a high number of tasks consistently, develop strong attention to detail, and use efficient tools or platforms that offer higher-paying projects. Building a reputation and acquiring specialized skills can also increase earning potential in this field.

Is data annotation real or fake?

Data annotation is a legitimate job involving labeling data such as images, text, or audio to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development. The work is real and essential for creating accurate AI systems.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

Does data annotation actually pay?

Data annotation jobs, including remote roles, typically pay hourly or per task rates that can range from a few cents to several dollars per annotation, depending on the complexity and platform. Many remote data annotation positions offer consistent pay, with some requiring basic skills in data labeling tools and attention to detail. Earnings can vary based on experience, the employer, and the volume of work completed.

What is the best data annotation company to work for?

There is no definitive best data annotation company, as opportunities vary based on factors like pay, work environment, and project types. Many companies in the industry offer remote positions with flexible schedules, and job seekers should research company reviews and requirements such as attention to detail and familiarity with annotation tools. Evaluating factors like pay rates, task variety, and company reputation can help identify suitable employers for data annotation roles.
What cities near Byram, CT are hiring for Remote Data Annotation jobs? Cities near Byram, CT with the most Remote Data Annotation job openings:

Senior Data Scientist | Upto $100/hr

Mercor

New York, NY • Remote

$100/hr

Full-time

Posted 27 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 Experts
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

  • Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices.
  • Design challenging data science tasks and write accurate, well-structured analytical solutions.
  • Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor.
  • Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Qualifications

Must-Have

  • 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning.
  • Ability to commit to 40 hours per week during weekdays for the duration of the engagement.
  • Strong written communication skills and the ability to explain analytical decisions and modeling choices clearly.

Preferred

  • Prior experience with data annotation, labeling, evaluation, or human feedback collection.
  • Experience with LLMs, AI systems, or agentic workflows; familiarity with agentic frameworks.

Compensation & Legal

  • W-2 employment with Cincinnatus LLC.

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.