AI Data Quality Specialist

12 hours ago

Las Piñas, National Capital Region, Philippines beBeeDataQuality Full time ₱4,000 - ₱8,000
Job Title: AI Data Quality Specialist

Achieve high-quality data standards with precision and attention to detail. As an AI Data Quality Specialist, you will be responsible for maintaining annotation standards and driving continuous improvements to ensure the accuracy and reliability of AI datasets.

Responsibilities:

  • Quality Audits: Conduct quality audits on annotated datasets to guarantee compliance with established guidelines and quality benchmarks.

  • Statistical Reporting: Utilize metrics such as F1 score and inter-annotator agreement to evaluate data quality and identify areas for improvement.

  • Root Cause Analysis: Analyze annotation errors, trends, and project documentation to pinpoint root causes and propose effective remediation strategies.

  • Edge-Case Management: Resolve and analyze edge-case annotations to ensure quality and identify opportunities for improvement.

  • Tooling: Effectively use annotation and quality control tools to perform reviews and track quality metrics.

  • Guidelines: Develop expertise in project guidelines and provide feedback for clarifications or improvements.

  • Continuous Improvement: Identify automation opportunities and contribute to documentation of quality standards and procedures.


Requirements:

  • Experience in data analysis with exposure to data quality and/or data annotation, preferably in an AI/ML context.

  • Familiarity with basic concepts of AI/ML pipelines and data.


Benefits:

  • Work from anywhere: Enjoy flexibility and work from your preferred location.

  • Every dataset is unique: Work on varied projects and audit, analyze, and improve AI/ML datasets.

  • Visible impact: Your quality checks and automation ideas will directly influence AI model performance.

  • Room to grow: Build expertise in AI data quality and expand your influence as projects evolve.

  • Mission-driven team: Collaborate with analysts, engineers, and stakeholders to create accurate, reliable AI models.


Keyword: DataQuality

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