Data Specialist (Remote)
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Key skills for this role
Role Overview
The client is seeking a Human Data Manager, New Grad for full-time work maintaining datasets used in AI model training and evaluation.
The role focuses on accuracy and relevance of labeled information, refinement of data pipelines, and improvement of annotation processes.
Key Skills for This Role
Full Job Posting
Role Overview
The client is seeking a Human Data Manager, New Grad for full-time work maintaining datasets used in AI model training and evaluation.
The role focuses on accuracy and relevance of labeled information, refinement of data pipelines, and improvement of annotation processes.
Key Responsibilities
- Review and validate human-labeled data for consistency and accuracy in AI training datasets.
- Identify and resolve annotation discrepancies by cross-referencing source materials and guidelines.
- Collaborate with cross-functional teams to refine annotation guidelines and improve data quality standards.
- Monitor and report data labeling performance metrics to track progress and identify trends.
- Document processes and maintain records of data sources, labeling rules, and quality checks.
Required Skills and Qualifications
- Experience with data annotation, labeling, or quality assurance processes is preferred.
- Familiarity with basic data validation techniques and attention to detail when reviewing datasets.
- Ability to follow structured guidelines and maintain consistency in data handling tasks.
- Basic understanding of AI and machine learning concepts and their dependence on high-quality training data is beneficial.
- Proficiency in using spreadsheets or data management tools to track and organize information.
Compensation
- Compensation is competitive and based on experience; no specific payment cadence is provided.
Workplace
- The role is remote and described as work from anywhere.
Opportunity Context
The position contributes to reliable AI systems through precise data management and provides exposure to machine learning workflows.
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