AI Data Quality Analyst

2 hours ago

Lipa City, Calabarzon, Philippines beBeeDataQuality Full time $55,000 - $75,000
Job Details

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Data Quality Specialist

Role Overview: With AI-driven solutions expanding across industries, ensuring high-quality training data is crucial for building reliable models. You will be responsible for maintaining annotation standards and driving continuous improvements to keep AI data accurate, efficient, and scalable.

Responsibilities:

  • Conduct thorough quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
  • Analyze metrics such as F1 score and inter-annotator agreement to evaluate data quality.
  • Identify and resolve annotation errors, trends, and project documentation to propose remediation strategies.
  • Expertly use annotation and quality control tools to perform reviews and track quality metrics.
  • Become a subject matter expert in project guidelines and provide feedback for clarifications or improvements.
  • Contribute to the development of quality standards and procedures.

Requirements:

  • 1+ years of experience as a data specialist with exposure to data quality and/or data annotation, ideally in an AI/ML context.
  • Familiarity with basic concepts of AI/ML pipelines and data.
  • Strong analytical and problem-solving skills with attention to detail.
  • Excellent written and verbal communication skills to clearly articulate quality issues and collaborate with diverse teams.
  • Ability to work independently and manage time effectively to meet deadlines.
  • Strong problem-solving, critical thinking, and continuous optimization mindset.

Benefits:

  • Work from anywhere you're most productive.
  • Every dataset presents a unique challenge: audit, analyze, and improve AI/ML datasets across varied projects.
  • Your quality checks and automation ideas will directly impact AI model performance.
  • You'll have opportunities to build expertise in AI data quality and expand your influence as projects grow.
  • Collaborate with analysts, engineers, and stakeholders to create accurate, reliable AI.

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