Data Specialist (Remote)

Role Summary

We are looking to hire a Data Specialist working remotely on a full-time basis. This role focuses on managing and maintaining high-quality datasets critical for AI model training and assessment. The position involves validating human-labeled data to ensure precision and relevance, enhancing annotation workflows, and supporting machine learning data pipeline improvements.

Primary Duties

• Examine and authenticate human-generated labels to guarantee consistency and accuracy in datasets used for AI training.
• Detect and address inconsistencies in annotation by cross-verifying with source materials and prescribed guidelines.
• Collaborate with various teams to update and refine annotation instructions and raise data quality benchmarks.
• Track and report metrics related to data annotation effectiveness to monitor progress and extract insightful patterns.
• Help with documenting procedures and maintaining comprehensive records of data origins, labeling criteria, and quality control measures.

Required Experience and Skills

• Preferable experience in data labeling, annotation, or quality assurance related fields.
• Knowledge of fundamental data validation approaches alongside meticulous attention when reviewing datasets.
• Capability to adhere to structured protocols and ensure uniformity in data operations.
• Basic familiarity with AI and machine learning principles and their reliance on quality training data is advantageous.
• Competence with spreadsheet software or data management tools for organizing and monitoring information.

Additional Information

This opportunity allows engagement with a prominent global company in the Technology, Information, and Internet sectors, contributing directly to robust AI system development. Candidates can gain hands-on experience with practical data applications within machine learning workflows.

Equal Opportunity

The employer values skills and merit above all and invites applications from qualified individuals regardless of their background, prior roles, or experience. Selection is strictly based on relevant technical skills and qualifications.