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Remote Data Labeling Jobs in Indiana (NOW HIRING)

This is a remote position. We do not offer visa sponsorship or assistance. Resumes and ... Establish practical foundations for dataset construction, labeling strategy, offline/online ...

$99.80K - $136.70K/yr

This is a remote position. We do not offer visa sponsorship or assistance. Resumes and ... Experience with data labeling, media processing (video/audio), or PDF manipulation. Engagement ...

Engineering & Science Job Schedule: Full time Remote: No The Company We build the machines that ... Provide technical writing and review of data or reports that will be incorporated into regulatory ...

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Remote Data Labeling information

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$9

$32

$71

How much do remote data labeling jobs pay per hour?

As of May 29, 2026, the average hourly pay for remote data labeling in Indiana is $32.20, according to ZipRecruiter salary data. Most workers in this role earn between $16.00 and $43.49 per hour, depending on experience, location, and employer.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

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

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

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

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.
What are the most commonly searched types of Data Labeling jobs in Indiana? The most popular types of Data Labeling jobs in Indiana are:
What are popular job titles related to Remote Data Labeling jobs in Indiana? For Remote Data Labeling jobs in Indiana, the most frequently searched job titles are:
What cities in Indiana are hiring for Remote Data Labeling jobs? Cities in Indiana with the most Remote Data Labeling job openings:
Infographic showing various Remote Data Labeling job openings in Indiana as of May 2026, with employment types broken down into 50% Full Time, 36% Part Time, 7% Temporary, and 7% Contract. Highlights an 100% Remote job distribution, with an average salary of $66,970 per year, or $32.2 per hour.

Data Labeling Specialist

Authenticx

Indianapolis, IN • Remote

Other

Posted 9 days ago


Job description

Position Summary

The Data Labeling Specialist is responsible for carefully reviewing healthcare-related conversations to determine whether a safety event has occurred. This role is highly transactional and relies on consistently applying a well-defined rubric to ensure accurate and objective identification of safety-related concerns. Your work is critical in supporting healthcare clients in maintaining compliance and improving outcomes. This role requires high accuracy and attention to detail while labeling high volumes of patient conversations.

Key Responsibilities

  • Conversation Review: Evaluate a high volume of healthcare-related conversations, using established rubrics to determine the presence or absence of safety events.
  • Rubric Adherence: Apply clearly defined labeling criteria with consistency and discipline to ensure reliability in safety event detection.
  • Quality and Accuracy: Deliver precise and objective reviews that align with expectations for labeling accuracy, supporting broader data integrity.
  • Team Collaboration: Participate in calibration efforts with teammates to promote labeling alignment across the team.
  • Feedback Adoption: Incorporate feedback from audits and performance checks to continually refine review accuracy and consistency.

Success Criteria:

  • Consistently apply rubric criteria to produce high-quality, objective safety labels validated through regular audits.
  • Achieve strong alignment with team standards and calibration practices.
  • Meet or exceed performance targets for daily and weekly review volumes while maintaining quality benchmarks.
  • Demonstrate reliability and consistency in handling high-volume, repetitive work while maintaining accuracy.

 

Key Skills and Abilities:

  • Objectivity: Strong ability to apply standards without bias or interpretation, even under repetitive conditions.
  • Attention to Detail: Exceptional focus on minute details to ensure safety flags are accurately identified.
  • Rubric-Driven Thinking: Comfort and discipline in working within a structured rubric-based decision framework.
  • Repetition Tolerance: High tolerance for performing repetitive tasks at scale while maintaining focus and precision.
  • Critical Thinking: Ability to assess edge cases within rubric guidelines to make consistent, sound judgments.
  • Quality Mindset: Motivated by accuracy and the importance of contributing to patient safety through diligence and care.
  • Written Communication: Capable of documenting decisions clearly and concisely when necessary.

Qualifications

  • 1-3 years of experience in customer support, health care, compliance, quality assurance or similar fields.
  • Strong analytical and critical thinking skills.
  • Ability to perform repetitive tasks with high attention to detail.
  • Experience in data labeling, transcription review, AI development or working with AI data is a plus.
  • Experience with pharmacovigilance is especially welcome.

 

Work Environment

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

  • This is a remote / virtual position

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee:

  • Is regularly required to sit and use hands to type and operate a computer and phone
  • Is frequently required to talk and hear
  • Is occasionally required to stand and walk
  • Must occasionally lift and/or move up to 25 pounds
  • Is occasionally required to reach with hands and arms, stoop, kneel, or crouch

Other

  • Time Management: Ability to manage time efficiently, balancing multiple projects and meeting tight deadlines.
  • Team Collaboration: Experience working cross-functionally with other teams (e.g., AI, data science) to achieve shared goals.
  • Problem-Solving: Strong problem-solving skills to identify inconsistencies or issues in labeling and find effective solutions.
  • Adaptability: Ability to adapt to changing priorities and project requirements.
  • Written Communication: Strong written communication skills to clearly document rubrics and provide detailed feedback during audits.
  • Technical Aptitude: Familiarity with data labeling software, spreadsheets, or other data management tools.