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Data Labelling Jobs in Indiana (NOW HIRING)

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 ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

Establish practical foundations for dataset construction, labeling strategy, offline/online ... Collaborate closely with engineering on data instrumentation, pipeline design, deployment, and ...

Data Protection Sr. Analyst

Indianapolis, IN · Hybrid

$84.80K - $100.70K/yr

Basic understanding of data classification/labeling, DLP policies and rules, and regulatory concepts (e.g., GDPR, HIPAA - awareness level). * PowerShell scripting or automation exposure is a plus.

Be Seen First

Data Center Technician Duties : · Pulling and routing CAT 5 or CAT 6 or Fiber cable in new construction and existing data center environment · Pulling Fiber · Dressing, labeling and terminating ...

Be Seen First

Perform cable management, labeling, and patching, ensuring all work adheres to established ... Collaborate with data center engineers, electricians, and other team members to coordinate ...

Data Protection Manager

Indianapolis, IN · On-site +1

$150.40K - $178.60K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

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Data Labelling information

See Indiana salary details

$43.8K

$157K

$231.7K

How much do data labelling jobs pay per year?

As of May 30, 2026, the average yearly pay for data labelling in Indiana is $157,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,000.00 and $161,800.00 per year, depending on experience, location, and employer.

What is a Data Labelling job?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

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

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

What are the typical daily responsibilities of a Data Labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.
What are the most commonly searched types of Data Labelling jobs in Indiana? The most popular types of Data Labelling jobs in Indiana are:
What are popular job titles related to Data Labelling jobs in Indiana? For Data Labelling jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Labelling jobs in Indiana look for? The top searched job categories for Data Labelling jobs in Indiana are:
Infographic showing various Data Labelling job openings in Indiana as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 97% Physical, and 3% Hybrid job distribution, with an average salary of $157,025 per year, or $75.5 per hour.

Data Labeling Specialist

Authenticx

Indianapolis, IN • Remote

Other

Posted 10 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.