Director of Data Quality, Gen AI

LabelBox • Full-time • San Francisco Bay Area • 2w ago

Your Day to Day

Recruit, train, and mentor a high-performing QA team.
Foster a culture of excellence, accountability, and continuous learning.
Design, implement, and optimize QA policies and procedures.
Apply advanced QC/QA methods, such as consensus scoring and statistical process control, to ensure quality standards. Identify workflow inefficiencies and implement best practices to enhance efficiency and reduce errors.
Drive initiatives for process improvements and automation in QA.
Develop long-term quality strategies aligned with company goals and industry trends.
Align QA objectives with overall business strategy.
Work with operations, product, engineering, and client teams to optimize annotation guidelines and processes.
Represent the QA function in client meetings and strategy sessions. Analyze quality metrics and KPIs to drive decision-making.
Prepare and present detailed reports to senior management.
Maintain compliance with industry standards and regulatory requirements. Stay updated on advancements in QA technologies and methodologies.

About You

Bachelor’s or Master’s degree in Data Science, Computer Science, Quality Management, or a related field.
Minimum of 5 years in quality management, particularly in data annotation or related industries.
Proven track record of leading QA teams and scaling processes in fast-paced environments.
Expert knowledge of QC/QA methods, including consensus scoring, Inter-Rater Reliability (IRR), and statistical process control.
Familiarity with data annotation tools, machine learning workflows, and statistical analysis software.
Experience with automation and AI-driven quality assurance tools is a plus.
Certifications such as Six Sigma Black Belt or ISO Quality Management are highly desirable.
Exceptional leadership, team-building, and communication skills.
Strong problem-solving and analytical abilities, with an innovative and data-driven mindset.
High adaptability and effectiveness in a fast-paced, client-centric environment.

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