Data Quality Lead

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Job Responsibilities:

Key Responsibilities:

Team Leadership and Management:

• Lead, mentor, and grow a team of data annotators and quality analysts.
• Ensure team members are trained, informed, and adhere to company standards and best practices.
• Oversee team performance, set goals, and conduct regular evaluations.

Strategic Oversight:

• Collaborate with senior management to define strategic goals and deliverables.
• Allocate resources and tasks efficiently among team members.
• Act as a bridge between the annotation team and other departments, ensuring effective communication.

Quality Assurance and Analysis:

• Oversee quality assurance processes and set benchmarks for performance and accuracy.
• Review and approve detailed reports on findings prepared by team members.
• Drive continuous improvement initiatives within the team based on analytics and performance metrics.

Technical Expertise:

• Stay updated with the latest in machine learning, data annotation, and natural language processing.
• Address complex technical challenges faced by the team.
• Provide guidance on advanced annotation techniques and quality analysis.

Linguistic and NLP Leadership:

• Guide the team in applying best practices in NLP and linguistics.
• Ensure consistent linguistic accuracy across all processed and annotated data.

Education: Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

• Prior experience in a leadership role within a data annotation or machine learning team.
• Proven track record of team management, mentorship, and performance optimization.
• Strong analytical skills with the ability to derive actionable insights from data.
• Deep understanding of machine learning models, data annotation, and quality assurance.
• Excellent communication and interpersonal skills.

Additional Job Details:

Additional Information:

This role primarily focuses on English US data sets; however, having experience with translation or multi-lingual data sets can be advantageous.