AI Data Quality and Annotation Expert
2 hours ago
TaskUs is a leading provider of outsourced digital services and customer experience solutions to innovative technology companies.
- Maintain annotation standards and drive continuous improvements to ensure the fidelity of training and evaluation datasets for building reliable models.
- Perform quality audits on annotated datasets, leverage metrics like F1 score and inter-annotator agreement to evaluate data quality, analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
- Resolve and analyze edge-case annotations to ensure quality and identify improvement areas, proficiently 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.
The ideal candidate will have 1+ years of experience as a data analyst with exposure to data quality and/or data annotation, ideally in an AI/ML context. Strong analytical and problem-solving skills, excellent written and verbal communication skills, and ability to work independently in a fast-paced environment are required. Familiarity with data annotation tools, experience with multi-modal AI/ML datasets, and knowledge of programming languages are nice to have.
Key Responsibilities:- Quality Audits – Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
- Statistical Reporting – Leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.
- Root Cause Analysis – Analyze 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 – Proficiently use 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.
Strong analytical and problem-solving skills, excellent written and verbal communication skills, and ability to work independently in a fast-paced environment are required. Familiarity with data annotation tools, experience with multi-modal AI/ML datasets, and knowledge of programming languages are nice to have.
Required Skills and Qualifications:- 1+ year of experience as a data analyst with exposure to data quality and/or data annotation, ideally in an AI/ML context.
- Strong analytical and problem-solving skills.
- Excellent written and verbal communication skills.
- Ability to work independently in a fast-paced environment.
- Familiarity with data annotation tools.
- Experience with multi-modal AI/ML datasets.
- Knowledge of programming languages.
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