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Data Annotation Project Manager Jobs in Milwaukee, WI

Gehc

Data Manager - AI Development

Waukesha, WI

Summary The Data Manager - AI Development is a key role within the AI Development team responsible ... Track annotation progress, throughput, and quality metrics. * Maintain annotation dashboards to ...

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

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

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

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 ...

SSP Innovations LLC

Data Project Manager

Milwaukee, WI · On-site +1

$51 - $69/hr

GIS Data Project Manager Description The GIS Data Project Manager is responsible for the planning, direction, coordination, implementation, execution, control and completion of project activities ...

SSP Innovations

Data Project Manager

Milwaukee, WI · Remote

$53 - $71.75/hr

GIS Data Project Manager Description The GIS Data Project Manager is responsible for the planning, direction, coordination, implementation, execution, control and completion of project activities ...

BetaNXT Inc

Project Manager

Brookfield, WI · On-site

Project Manager About BetaNXT BetaNXT is a leading provider of frictionless wealth management ... BetaNXT is a premier provider of technology, data, and operations as services to a rich client base ...

Rockwell Automation, Inc.

Project Manager

Milwaukee, WI · On-site

Manage projects of varying size and complexity across North American manufacturing sites. * Define ... Proficient in using data science and analytics tools to support project insights and performance ...

Rockwell Automation

Project Manager

Milwaukee, WI · Hybrid

Manage projects of varying size and complexity across North American manufacturing sites. * Define ... Proficient in using data science and analytics tools to support project insights and performance ...

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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 May 29, 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.

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.

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 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 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 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:
Data Annotation Project Manager jobs near you
Infographic showing various Data Annotation Project Manager job openings in Milwaukee, WI as of May 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $117,852 per year, or $56.7 per hour.
Data Manager - AI Development

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Posted 17 days ago

GE HealthCare rating

8.5

Company rating: 8.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

61st of 415 rated machine equipment manufacturers

Job description

Job Description Summary
The Data Manager - AI Development is a key role within the AI Development team responsible for planning, coordinating, tracking, and governing data used to develop AI enabled medical device features. This role works closely with AI/ML engineers to define data needs for AI features, coordinates with internal and external data collection teams/clinical team, oversees annotation activities, and ensures data readiness, traceability, and compliance throughout the AI development lifecycle.
The role is execution focused and coordination driven, ensuring that the right data is available, prepared, and documented at the right time to support AI feature development, evaluation, and regulatory readiness. Strong planning, communication, and organizational skills are essential for success in this role.
Please note - this is a full time, onsite role located in Waukesha, WI.
Job Description
Roles and Responsibilities
Key Roles and Responsibilities
1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

Required Qualifications
  • 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.

Desired Characteristics
  • 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

Why Join Us?
  • Be at the forefront of AI-driven healthcare innovation.
  • Collaborate with a multidisciplinary team passionate about improving patient outcomes.
  • Shape the future of regulatory processes for cutting-edge medical technologies.

We will not sponsor individuals for employment visas, now or in the future, for this job opening.
Additional Information
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: No

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