This is a remote / virtual position Physical Demands The physical demands described here are ... Familiarity with data labeling software, spreadsheets, or other data management tools.
This is a remote / virtual position Physical Demands The physical demands described here are ... Familiarity with data labeling software, spreadsheets, or other data management tools.
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 ...
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 ...
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 ...
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 ...
Product Compliance Engineer
Michigan City, IN · On-site +1
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 ...
Product Compliance Engineer
Michigan City, IN · On-site +1
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 ...
Data Labeler Remote information
What are the key skills and qualifications needed to thrive as a Data Labeler Remote, and why are they important?
To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.
What are some common challenges faced by remote data labelers and how can they be managed?
Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.
What does a remote data labeler do?
A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.
What is the difference between Data Labeler Remote vs Data Annotator Remote?
| Aspect | Data Labeler Remote | Data Annotator Remote |
|---|---|---|
| Credentials | Basic computer skills, attention to detail | Basic computer skills, attention to detail |
| Work Environment | Remote, flexible hours | Remote, flexible hours |
| Industry Usage | Common in AI/ML data preparation | Common in AI/ML data preparation |
| Job Focus | Labeling data points for machine learning | Annotating data for training AI models |
Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.
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What are popular job titles related to Data Labeler Remote jobs in Indiana? For Data Labeler Remote jobs in Indiana, the most frequently searched job titles are:
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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.