QA Analyst Lead

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Job Responsibilities:

The ideal candidate will possess both technical prowess in machine learning and natural language processing, along with strong leadership skills to guide and mentor their team. 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.