AI Data Quality Expert

6 hours ago

Iloilo City, Western Visayas, Philippines beBeeDataQuality Full time $60,000 - $80,000
AI Data Quality Specialist

We are looking for a meticulous and detail-focused individual to join our team as an AI Data Quality Specialist. In this role, you will be responsible for ensuring the fidelity of training and evaluation datasets, which is crucial for building reliable models.

As an AI-driven solutions expand across industries, we need a diligent Data Quality Analyst who can maintain annotation standards and drive continuous improvements. If you have experience in data quality and/or data annotation, ideally in an AI/ML context, we want to hear from you.

Your primary focus will be on performing quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks. You will also be responsible for statistical reporting, root cause analysis, edge-case management, tooling, and continuous improvement.

To excel in this role, you should have strong analytical and problem-solving skills with an exceptional eye for detail. Excellent written and verbal communication skills are also essential to clearly articulate quality issues and collaborate with diverse teams.

We offer a positive work environment where you can grow professionally and develop new skills. Our inclusive culture supports internal mobility, and we prioritize employee well-being with competitive salaries and comprehensive benefits.

You will work independently in a fast-paced environment with a focus on detail and strategic priorities. If you are proactive, adaptable, and not afraid to speak up, we encourage you to apply.

This is a remote job opportunity, allowing you to work from anywhere you're most productive. Every dataset is unique, and your quality checks and automation ideas will influence AI model performance. There is room to grow, and you'll collaborate with analysts, engineers, and stakeholders to create accurate, reliable AI.

The impact you'll make includes guarding data integrity through audits, pinpointing and resolving annotation issues, optimising annotation processes, collaborating and coaching, and tracking and communicating quality performance.

  • Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.

  • Conduct statistical reporting to evaluate data quality.

  • Analyse annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.

  • Manage edge-case annotations to ensure quality and identify improvement areas.

  • Use annotation and quality control tools to perform reviews and track quality metrics.

  • Become an expert in project guidelines and provide feedback for clarifications or improvements.

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

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