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Data Annotation Services Jobs in Wisconsin (NOW HIRING)

... annotation, and preparation activities. • Support creation and maintenance of AI data planning ... GE Healthcare provides a wide range of medical technologies and services to healthcare providers ...

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

SAP SME Consultant - ABAP

Neenah, WI · On-site

$63.25 - $85.75/hr

Core Data Services annotations * Business Object Processing Framework (BOPF) Data Handling ... Business logic annotation and transformation rules * Functional-to-technical traceability

Data Annotation Services information

What are the key skills and qualifications needed to thrive in data annotation services?

To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.

What is the difference between Data Annotation Services vs Data Labeling Specialists?

AspectData Annotation ServicesData Labeling Specialists
CredentialsTypically no formal credentials required; focus on trainingOften have training in specific tools or industry standards
Work EnvironmentCollaborative, often remote or in-office teamsSimilar, working in teams or independently on labeling tasks
Industry UsageUsed by AI/ML companies for training datasetsEmployed in similar settings, focusing on labeling data for AI models
Search & Comparison IntentUnderstanding services offered for data preparationLooking for roles or tasks related to data labeling

Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.

What are some common challenges faced when working in data annotation services, and how can I address them?

In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.

What are data annotation services?

Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.
What are popular job titles related to Data Annotation Services jobs in Wisconsin? For Data Annotation Services jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Annotation Services jobs in Wisconsin look for? The top searched job categories for Data Annotation Services jobs in Wisconsin are:

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Re-posted 24 days ago


GE HealthCare rating

8.4

Company rating: 8.4 out of 10

Based on 137 frontline employees who took The Breakroom Quiz

98th 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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