... medical imaging data formats and annotation tools (e.g., V7). • Exposure to regulated development environments (medical devices, healthcare software, or similar). • Understanding of data ...
... medical imaging data formats and annotation tools (e.g., V7). • Exposure to regulated development environments (medical devices, healthcare software, or similar). • Understanding of data ...
... them in various annotation and data management applications. A key project is the Advancing ... The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to ...
... them in various annotation and data management applications. A key project is the Advancing ... The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to ...
... them in various annotation and data management applications. A key project is the Advancing ... The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to ...
... them in various annotation and data management applications. A key project is the Advancing ... The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to ...
Research Scientist I
Milwaukee, WI · On-site
... the Medical College of Wisconsin seeks a highly motivated Research Scientist to join a ... in various software, annotation, and data management applications. The incumbent will gain ...
Research Scientist I
Milwaukee, WI · On-site
... the Medical College of Wisconsin seeks a highly motivated Research Scientist to join a ... in various software, annotation, and data management applications. The incumbent will gain ...
... the Medical College of Wisconsin seeks a highly motivated Research Scientist to join a ... in various software, annotation, and data management applications. The incumbent will gain ...
... the Medical College of Wisconsin seeks a highly motivated Research Scientist to join a ... in various software, annotation, and data management applications. The incumbent will gain ...
Monitor and maintain medical equipment during the procedure. Adjust and calibrate pressure ... Monitor and record all procedural data (e.g. injection data, physiologic data, administered ...
Quick apply
Monitor and maintain medical equipment during the procedure. Adjust and calibrate pressure ... Monitor and record all procedural data (e.g. injection data, physiologic data, administered ...
Medical Data Annotation information
See Wisconsin salary details
$9 - $12.51
14% of jobs
$13.51 is the 25th percentile. Wages below this are outliers.
$12.51 - $16.02
39% of jobs
$19.06 is the 75th percentile. Wages above this are outliers.
$16.02 - $19.54
26% of jobs
$19.54 - $23.05
9% of jobs
$23.05 - $26.56
2% of jobs
$26.56 - $30.07
6% of jobs
$30.07 - $33.58
4% of jobs
$33.58 - $37.10
0% of jobs
$37.10 - $40.61
0% of jobs
$40.61 - $44.12
0% of jobs
$44.12 - $47.63
0% of jobs
$8
$20
$47
How much do medical data annotation jobs pay per hour?
As of Jul 25, 2026, the average hourly pay for medical data annotation in Wisconsin is $20.38, according to ZipRecruiter salary data. Most workers in this role earn between $13.61 and $20.85 per hour, depending on experience, location, and employer.
What is a Medical Data Annotation job?
A Medical Data Annotation job involves labeling and categorizing medical data, such as patient records, medical images, and clinical notes, to help train artificial intelligence (AI) models. Annotators ensure that AI systems can accurately interpret medical information by applying domain-specific knowledge and following strict guidelines. This role requires attention to detail, familiarity with medical terminology, and sometimes collaboration with healthcare professionals to ensure accuracy.
What are the key skills and qualifications needed to thrive in the Medical Data Annotation position, and why are they important?
To thrive in Medical Data Annotation, you need a solid understanding of medical terminology, attention to detail, and familiarity with clinical or healthcare data formats, often backed by relevant coursework or experience in healthcare or life sciences. Proficiency with data annotation platforms, medical coding software, and sometimes certifications like HIPAA compliance are highly valued. Strong communication skills, a high level of accuracy, and the ability to work both independently and collaboratively set standout candidates apart. These skills help ensure data integrity and support the development of reliable AI-powered healthcare solutions.
What are the typical challenges faced in Medical Data Annotation roles?
One of the main challenges in Medical Data Annotation is accurately interpreting complex medical information and ensuring consistency across large datasets. Annotators often work with sensitive patient data, so maintaining confidentiality and adhering to strict data security protocols is essential. The work can be repetitive and detail-oriented, but it is crucial for training reliable medical AI systems. Successful Medical Data Annotation professionals stay motivated by understanding the impact of their work on advancing medical research and patient care.
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 Medical Data Annotation jobs in Wisconsin? For Medical Data Annotation jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Medical Data Annotation jobs in Wisconsin look for? The top searched job categories for Medical Data Annotation jobs in Wisconsin are:
GE HealthCare rating
8.4
Based on 137 frontline employees who took The Breakroom Quiz
82nd of 433 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:
Every day millions of people feel the impact of our intelligent devices, advanced analytics and artificial intelligence. Founded in 1989, the company is headquartered in Oslo, NOR, with a team of 10001+ employees. The company is currently Late Stage.
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:
Every day millions of people feel the impact of our intelligent devices, advanced analytics and artificial intelligence. Founded in 1989, the company is headquartered in Oslo, NOR, with a team of 10001+ employees. The company is currently Late Stage.
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