AI Data Labeling & Quality Analyst

Hire Feed; Philippines; On-site; PHP 300,000 - 420,000; Full time

Job summary

Hire Feed is seeking a Human Data Manager, New Grad to join as a full-time team member in the Philippines. The role focuses on maintaining high-quality datasets used for AI model training and evaluation, ensuring accuracy and relevance of labeled information.

You will review labeled data, resolve inconsistencies, and collaborate with teams to refine annotation guidelines while tracking data quality metrics and documenting data sources and rules.

Qualifications

• Experience with data annotation, labeling, or quality assurance processes is preferred.
• Familiarity with basic data validation techniques and attention to detail in reviewing datasets.
• Ability to follow structured guidelines and maintain consistency in data handling tasks.
• Basic understanding of AI/ML concepts and their dependence on high-quality training data is beneficial.
• Proficiency in using spreadsheets or data management tools to track and organize information.

Responsibilities

• Review and validate human-labeled data to ensure consistency and accuracy for AI training datasets.
• Identify and resolve discrepancies in data annotations by cross-referencing source materials and guidelines.
• Collaborate with cross-functional teams to refine annotation guidelines and improve data quality standards.
• Monitor and report on data labeling performance metrics to track progress and identify trends.
• Assist in documenting processes and maintaining records of data sources, labeling rules, and quality checks.

Skills

Data annotation

Data validation

Guideline adherence

AI/ML basics

Spreadsheet management

Job description

Hire Feed is seeking a Human Data Manager, New Grad to join as a full-time team member in the Philippines. The role focuses on maintaining high-quality datasets used for AI model training and evaluation, ensuring accuracy and relevance of labeled information.

You will review labeled data, resolve inconsistencies, and collaborate with teams to refine annotation guidelines while tracking data quality metrics and documenting data sources and rules.