
Data Quality Specialist
12 hours ago
We are seeking a skilled Data Quality Specialist to join our team. As a Data Quality Analyst, you will play a critical role in ensuring the accuracy and reliability of our AI models.
Your primary responsibility will be to perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks. You will also leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.
Key Responsibilities:
- Quality Audits: Conduct thorough reviews of annotated datasets to identify areas for improvement and implement corrective actions.
- Metrics Evaluation: Analyze data quality metrics to identify trends and opportunities for improvement.
- Root Cause Analysis: Investigate annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
- Edge-Case Management: Resolve and analyze edge-case annotations to ensure quality and identify improvement areas.
- Tooling: Utilize annotation and quality control tools to perform reviews and track quality metrics.
- Guidelines: Become an expert in project guidelines and provide feedback for clarifications or improvements.
- Continuous Improvement: Identify automation opportunities and contribute to documentation of quality standards and procedures.
To be successful in this role, you will need to possess the following skills and qualifications:
- Strong Analytical Skills: You must have exceptional analytical and problem-solving skills with an eye for detail.
- Excellent Communication Skills: You will need to clearly articulate quality issues and collaborate with diverse teams.
- Time Management: You must be able to work independently and manage your time effectively to meet deadlines.
- Problem-Solving Mindset: You will need to approach problems with a critical thinking and continuous optimization mindset.
As a Data Quality Specialist, you will enjoy the following benefits:
- Remote Work: You will have the flexibility to work remotely from anywhere you are most productive.
- Unique Datasets: Every dataset is unique, requiring your attention to detail and expertise.
- Visible Impact: Your quality checks and automation ideas will influence AI model performance.
- Room to Grow: You will have the opportunity to build expertise in AI data quality and expand your influence as projects grow.
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