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Data Annotation Project Manager Jobs in Milwaukee, WI

TSMG

AI/ML Data Contributor

Milwaukee, WI · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Whirlpool

Project Manager

Mount Pleasant, WI · On-site

Manage data in multiple systems to support project health data tracking and reporting. * Tracking, Maintenance, and reporting of project expenses and capital calendar. * Support project Bill of ...

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Data Annotation Project Manager information

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How much do data annotation project manager jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for data annotation project manager in Milwaukee, WI is $56.66, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $66.30 per hour, depending on experience, location, and employer.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards using tools like labeling platforms and project management software.

Does data annotation actually pay?

Data annotation project managers oversee tasks where annotators are paid for labeling data used in machine learning. The pay for annotators varies depending on the platform, project complexity, and experience, with many earning hourly wages or per-task rates. The role of a project manager involves coordinating these efforts and ensuring quality, often with a salary or contract-based compensation.

What are the key skills and qualifications needed to thrive as a Data Annotation Project Manager, and why are they important?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

How hard is it to get hired by data annotation?

Getting hired as a data annotation project manager typically requires relevant experience in project management, familiarity with annotation tools, and strong organizational skills. The role often involves coordinating teams and ensuring quality standards, with some positions requiring certifications or prior experience in data labeling environments. Competition varies depending on the company and location, but demonstrating technical knowledge and management ability can improve chances of hiring.

What is the salary of data annotation manager?

The salary of a Data Annotation Project Manager typically ranges from $60,000 to $100,000 annually, depending on experience, location, and company size. They often oversee teams using annotation tools and ensure quality standards are met in data labeling projects.

What are some common challenges faced by Data Annotation Project Managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What is a Data Annotation Project Manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.
What are popular job titles related to Data Annotation Project Manager jobs in Milwaukee, WI? For Data Annotation Project Manager jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Data Annotation Project Manager jobs in Milwaukee, WI look for? The top searched job categories for Data Annotation Project Manager jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Data Annotation Project Manager jobs? Cities near Milwaukee, WI with the most Data Annotation Project Manager job openings:
Data Annotation Project Manager jobs near you
Data Manager - AI Development

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Re-posted 27 days ago

GE HealthCare rating

8.4

Company rating: 8.4 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

78th of 427 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 is a multinational company that manufactures wide range of medical equipment. Founded in 1987, the company is headquartered in Buc, FRA, with a team of 10001+ employees. The company is currently Late Stage.

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