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Home Based Medical Data Annotation Jobs in Wisconsin

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

WI · On-site

Zaventem, Belgium | Full time | Home-based | R1560112 "I like that we're different. I like that we ... If you like an organization that has a variety of opportunities, from IT to big data to AI to ...

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Home Based Medical Data Annotation information

What are some common challenges faced by professionals working in home-based medical data annotation, and how can they be managed?

One common challenge in home-based medical data annotation is maintaining accuracy and consistency when labeling complex medical images or records, as errors can impact critical healthcare outcomes. Working remotely may also lead to feelings of isolation or difficulty staying updated with annotation guidelines. To manage these challenges, it's important to establish a quiet, dedicated workspace, participate in regular virtual team meetings, and utilize provided training resources. Staying engaged with peers through communication channels and seeking feedback from supervisors can also help ensure high-quality work and ongoing professional development.

What are the key skills and qualifications needed to thrive as a Home Based Medical Data Annotation Specialist, and why are they important?

To thrive as a Home Based Medical Data Annotation Specialist, you need a solid understanding of medical terminology, attention to detail, and experience with data labeling—often supported by a background in healthcare or life sciences. Familiarity with annotation platforms, EHR systems, and relevant data security protocols is typically required, and some employers may prefer certifications in medical coding or data management. Strong organizational skills, self-motivation, and effective written communication help individuals excel in remote, deadline-driven environments. These competencies ensure accurate, high-quality data labeling that is essential for developing reliable AI systems in healthcare.

What is the difference between Home Based Medical Data Annotation vs Home Based Medical Transcription?

AspectHome Based Medical Data AnnotationHome Based Medical Transcription
Required CredentialsBasic medical knowledge, attention to detailMedical terminology, transcription skills, sometimes certification
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, data labeling for healthcare AI modelsConverting audio to written reports for medical records
Common Search/ComparisonYesYes

Home Based Medical Data Annotation involves labeling medical images and data to train AI systems, requiring attention to detail and basic medical knowledge. In contrast, Home Based Medical Transcription focuses on converting audio recordings into written medical reports, often needing transcription skills and familiarity with medical terminology. Both roles are remote and industry-specific, but they serve different purposes within healthcare technology and documentation.

What is home based medical data annotation?

Home based medical data annotation involves labeling and categorizing medical data, such as images, audio, or text, from the comfort of your home. Annotators help train artificial intelligence (AI) systems by identifying and marking relevant information, such as highlighting tumors in X-rays or transcribing medical notes. This role is essential for improving the accuracy and efficiency of AI tools used in healthcare diagnostics, research, and patient care. Typically, it requires attention to detail, a basic understanding of medical terminology, and familiarity with annotation tools.
What are the most commonly searched types of Medical Data Annotation jobs in Wisconsin? The most popular types of Medical Data Annotation jobs in Wisconsin are:
What are popular job titles related to Home Based Medical Data Annotation jobs in Wisconsin? For Home Based Medical Data Annotation jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Home Based Medical Data Annotation jobs in Wisconsin look for? The top searched job categories for Home Based Medical Data Annotation jobs in Wisconsin are:
What cities in Wisconsin are hiring for Home Based Medical Data Annotation jobs? Cities in Wisconsin with the most Home Based Medical Data Annotation job openings:
Infographic showing various Home Based Medical Data Annotation job openings in Wisconsin as of July 2026, with employment types broken down into 2% As Needed, 64% Full Time, 25% Part Time, 2% Temporary, 5% Contract, and 2% Nights. Highlights an 82% In-person, 4% Hybrid, and 14% Remote job distribution.

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Re-posted 20 days ago


GE HealthCare rating

8.4

Company rating: 8.4 out of 10

Based on 137 frontline employees who took The Breakroom Quiz

99th of 487 rated machine equipment manufacturers


Job description

Job Summary:
GE HealthCare is a leader in healthcare innovation, and they are seeking a Data Manager for their AI Development team. This role is responsible for planning, coordinating, tracking, and governing data used to develop AI-enabled medical device features, working closely with AI/ML engineers and various stakeholders to ensure data readiness and compliance throughout the development lifecycle.
Responsibilities:
• AI Data Planning & Requirements
• Partner with AI/ML engineers and technical leads to define data requirements for AI features, including dataset scope, diversity, and usage intent.
• Translate feature and model needs into clear data requirements that guide collection, annotation, and preparation activities.
• Support creation and maintenance of AI data planning artifacts aligned with internal Quality Management System (QMS) requirements.
• Data Collection Coordination
• Coordinate with centralized and distributed data collection teams to support AI development needs.
• Track data sourcing activities across multiple programs and stakeholders.
• Maintain data collection dashboards that provide visibility into status, coverage, risks, and gaps.
• Track data collection and annotation budget.
• Annotation & Labeling Oversight
• Coordinate data annotation activities with internal teams and external vendors.
• Track annotation progress, throughput, and quality metrics.
• Maintain annotation dashboards to ensure timely delivery aligned with AI development milestones.
• Data Governance & Compliance Support
• Support execution of AI data management practices including:
• Data control planning
• Data segregation between training, holdout, and testing datasets
• Data preparation and inclusion criteria
• Data traceability and usage documentation
• Ensure datasets are properly documented and traceable to their original sources to support audits and regulatory submissions.
• Act as a point of coordination to ensure data activities align with applicable QMS work instructions for AI development.
• Program Tracking & Communication
• Serve as the central coordination point for AI data activities across engineering, data operations, and program teams.
• Proactively communicate status, risks, and dependencies to stakeholders.
• Support planning reviews, design reviews, and readiness discussions with accurate data status reporting.
Qualifications:
Required:
• Bachelor’s degree in Engineering, Computer Science, Data Science, Biomedical Engineering, or a related technical discipline with 4 years of experience.
• Experience in data management, data operations, or program coordination roles supporting technical or engineering teams.
• Demonstrated ability to plan, track, and coordinate complex workflows across multiple stakeholders.
• Strong written and verbal communication skills, with the ability to translate technical needs into actionable plans.
• Experience creating and maintaining dashboards (eg. PowerBI, excel, smartsheet) trackers, or reports for operational visibility.
• Familiarity with structured data workflows(eg. SQL), including data collection, annotation, and dataset organization(eg. Python).
• Ability to work effectively in cross‑functional teams within a regulated or quality‑driven environment.
Preferred:
• Experience supporting AI / machine learning development teams, particularly in healthcare or medical devices.
• Familiarity with AI data lifecycle concepts, including training, validation, and testing datasets.
• Knowledge of medical imaging data formats and annotation tools (e.g., V7).
• Exposure to regulated development environments (medical devices, healthcare software, or similar).
• Understanding of data governance concepts such as data traceability, segregation, and controlled usage.
• Experience coordinating external vendors or annotation partners.
• Comfort working with ambiguity and evolving requirements in early‑stage AI feature development.
• Experience with Microsoft Forms
Company:
GE Healthcare provides a wide range of medical technologies and services to healthcare providers and researchers. It is a sub-organization of General Electric. Founded in 1892, the company is headquartered in Chicago, USA, with a team of 10001+ employees. The company is currently Late Stage.

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