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Data Annotation Project Manager Jobs in Milwaukee, WI

Alignerr

Oncology Clinical Researcher

Milwaukee, WI · Remote

Experienced in designing and managing oncology clinical trials from protocol development through ... Experience with data annotation, data quality review, or evaluation systems * Background in ...

Alignerr

Medical Science Liaison (MSL)

Milwaukee, WI · Remote

... projects that matter. * Organization : Alignerr * Type : Hourly Contract * Location : Remote ... Experience with data annotation, content evaluation, or AI model review workflows * Familiarity ...

Electric Pump

Project Manager

Franksville, WI · On-site

Analyze KPIs and production data to inform project decisions and prioritization Safety, Quality ... Experience managing contractors and capital equipment installations Work Environment

Electric Pump

Project Manager

Franksville, WI · On-site

Analyze KPIs and production data to inform project decisions and prioritization Safety, Quality ... Experience managing contractors and capital equipment installations Work Environment

Xylem

Project Manager

Waukesha, WI

Strong understanding of project management principles and practices Strong analytical skills with the ability to interpret complex data. Proficiency in project management tools and software (e.g., MS ...

Xylem

Project Manager

Waukesha, WI · On-site

... data. • Proficiency in project management tools and software (e.g., MS Project, Asana, Trello). • Excellent written and verbal communication skills. • Ability to work independently and ...

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Data Annotation Project Manager information

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$16

$56

$79

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.

Oncology Clinical Researcher

Alignerr

Milwaukee, WI • Remote

Full-time

Posted 17 days ago

Job description

Oncology Clinical Researcher (AI Training)
About the Role
What if your deep knowledge of cancer clinical trials could directly shape how AI understands and reasons about oncology - influencing research tools used by scientists and clinicians worldwide?
We're looking for experienced Oncology Clinical Researchers to bring real-world expertise into AI development workflows. You'll review, evaluate, and improve AI-generated oncology content - ensuring that the models powering tomorrow's cancer research are grounded in rigorous clinical science, regulatory standards, and patient-centered evidence.
This is a fully remote, flexible contract role. No AI background required - just deep oncology expertise and a sharp eye for clinical accuracy.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 10-40 hours/week
    • What You'll Do
    • Review and evaluate AI-generated oncology content for clinical accuracy, regulatory alignment, and scientific rigor
    • Apply your expertise in trial design - protocols, patient enrollment, endpoints, and ethics - to assess how well AI captures real-world standards
    • Analyze AI outputs related to cancer trial data, including safety profiles, efficacy results, and biomarker interpretation
    • Evaluate AI-generated regulatory and scientific content against FDA, EMA, and ICH standards
    • Flag errors, gaps, or misleading outputs and provide structured, expert feedback
    • Work independently and asynchronously - fully on your own schedule
    Who You Are
    • Experienced in designing and managing oncology clinical trials from protocol development through data readout
    • Strong background in analyzing oncology clinical data - endpoints, safety profiles, biomarkers, and statistical outputs
    • Familiar with regulatory submission standards for agencies such as the FDA or EMA
    • Detail-oriented with a systematic approach to evaluating complex scientific content
    • Comfortable working independently and delivering high-quality written feedback
    • No prior AI or tech experience required
    Nice to Have
    • Experience with data annotation, data quality review, or evaluation systems
    • Background in translational oncology, biomarker research, or precision medicine
    • Familiarity with clinical trial phases across solid tumors or hematologic malignancies
    • Prior involvement in regulatory submissions, publications, or clinical guideline development
    Why Join Us
    • Work directly on frontier AI systems transforming the future of cancer research
    • Fully remote and flexible - work when and where it suits you
    • Freelance autonomy with the structure of meaningful, high-stakes scientific work
    • Shape how AI models understand real oncology data - a direct, tangible contribution to the field
    • Collaborate with leading AI research teams and labs on cutting-edge projects
    • Potential for ongoing work and contract extension as new projects launch

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