... annotation, and preparation activities. • Support creation and maintenance of AI data planning artifacts aligned with internal Quality Management System (QMS) requirements. • Data Collection ...
... annotation, and preparation activities. • Support creation and maintenance of AI data planning artifacts aligned with internal Quality Management System (QMS) requirements. • Data Collection ...
The incumbent will gain experience managing existing, as well as starting new, ontologies and using them in various annotation and data management applications. A key project is the Advancing ...
The incumbent will gain experience managing existing, as well as starting new, ontologies and using them in various annotation and data management applications. A key project is the Advancing ...
The incumbent will gain experience managing existing, as well as starting new, ontologies and using them in various annotation and data management applications. A key project is the Advancing ...
The incumbent will gain experience managing existing, as well as starting new, ontologies and using them in various annotation and data management applications. A key project is the Advancing ...
Research Scientist I
Milwaukee, WI · On-site
... annotation, and data management applications. The incumbent will gain experience in the theory and practice of biomedical, health, and behavioral ontologies, including advanced ontology development ...
Research Scientist I
Milwaukee, WI · On-site
... annotation, and data management applications. The incumbent will gain experience in the theory and practice of biomedical, health, and behavioral ontologies, including advanced ontology development ...
... annotation, and data management applications. The incumbent will gain experience in the theory and practice of biomedical, health, and behavioral ontologies, including advanced ontology development ...
... annotation, and data management applications. The incumbent will gain experience in the theory and practice of biomedical, health, and behavioral ontologies, including advanced ontology development ...
Russian Data Annotation Manager information
See Milwaukee, WI salary details
$30.5K - $43.2K
7% of jobs
$43.2K - $55.8K
8% of jobs
$64.3K is the 25th percentile. Wages below this are outliers.
$55.8K - $68.4K
14% of jobs
$68.4K - $81.1K
18% of jobs
The median wage is $83.3K / yr.
$81.1K - $93.7K
15% of jobs
$93.7K - $106.3K
7% of jobs
$115.8K is the 75th percentile. Wages above this are outliers.
$106.3K - $118.9K
7% of jobs
$118.9K - $131.6K
6% of jobs
$131.6K - $144.2K
6% of jobs
$144.2K - $156.8K
4% of jobs
$156.8K - $169.5K
6% of jobs
$30.5K
$95.7K
$169.5K
How much do russian data annotation manager jobs pay per year?
As of Jul 31, 2026, the average yearly pay for russian data annotation manager in Milwaukee, WI is $95,711.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $123,600.00 per year, depending on experience, location, and employer.
What is a Russian Data Annotation Manager job?
A Russian Data Annotation Manager oversees the process of labeling and annotating data in the Russian language for machine learning and AI projects. They manage teams of annotators, ensure data quality, and optimize workflows to meet project requirements. This role requires fluency in Russian, attention to detail, and experience with annotation tools. Additionally, they collaborate with engineers and linguists to refine annotation guidelines for accurate model training.
What are some common challenges faced by Russian Data Annotation Managers, and how do they overcome them?
Russian Data Annotation Managers often encounter challenges related to maintaining consistency and accuracy across large, multilingual annotation teams, especially when dealing with nuanced language data. They address these issues by developing clear guidelines, conducting regular quality checks, and providing ongoing training to annotators. Collaboration with data scientists, project managers, and quality assurance personnel is also important to quickly resolve ambiguities and implement feedback. By fostering open communication and setting clear expectations, managers help ensure project standards are met and team members feel supported.
What are the key skills and qualifications needed to thrive in the Russian Data Annotation Manager position, and why are they important?
To thrive as a Russian Data Annotation Manager, you need fluency in Russian, experience with data annotation processes, and strong organizational abilities, often supported by a background in linguistics, computer science, or a related field. Familiarity with annotation platforms, data labeling tools, and project management software is commonly required. Leadership, attention to detail, and effective communication are key soft skills that help excel in managing diverse annotation teams. These skills are essential for ensuring high-quality data outputs and efficient project delivery in multilingual technology environments.
What are popular job titles related to Russian Data Annotation Manager jobs in Milwaukee, WI? For Russian Data Annotation Manager jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Russian Data Annotation Manager jobs in Milwaukee, WI look for? The top searched job categories for Russian Data Annotation Manager jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Russian Data Annotation Manager jobs? Cities near Milwaukee, WI with the most Russian Data Annotation Manager job openings:
GE HealthCare rating
8.4
Based on 137 frontline employees who took The Breakroom Quiz
99th 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.
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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