Data Quality Specialist with Spanish (Night shift)

at  TELUS Digital

We are seeking a Data Quality Specialist responsible for ensuring the quality of data annotation, refining scoring rubrics, and driving process improvements. The role involves conducting data reviews, managing quality assessments, and ensuring that project workflows consistently meet high-quality standards.

REQUIREMENTS

• Min.C2 proficiency in Spanish
• Min. B2 proficiency in English
• Advanced Google Workspace skills
• Awareness of ethical considerations in AI, especially in advertising
• Proficiency in evaluating data and identifying issues or deviations from guidelines.
• Strong ability to resolve conflicts and foster collaboration within global cross-functional teams.
• Strong communication skills for explaining evaluations, proposing solutions, and providing process insights.
• Detail-oriented with a deep understanding of annotation guidelines, ensuring accuracy and consistency in AI data.
• Creative problem-solver, able to tackle challenges in evolving and undefined scenarios.

EXPERIENCE

• At least 1 year of experience in roles such as Statistics, Machine Learning, Marketing, Reporting, Quality Assurance, or related fields.
• Previous experience in quality control, with a strong understanding of data labeling, annotation, and evaluation methodologies.

• Assign quality scores to data, monitor workflow performance through metric analysis, identify gaps, categorize errors, and conduct trend analysis against project objectives.
• Conduct trial runs of data annotation protocols to gain proficiency in tools and quality assurance practices.
• Develop and continuously update data annotation procedures and guidelines to ensure compliance and consistency.
• Collaborate with clients to resolve challenges, propose workflow improvements, and enhance processes.
• Conduct training sessions and calibration meetings to maintain consistent annotation quality and ensure clear understanding of processes.
• Perform quality assessments, create and validate scoring rubrics, evaluate annotated data to ensure alignment with quality standards, and conduct statistical analysis of performance metrics to drive continuous improvement.
• Handle inquiries from PgMs, clarify labeling guidelines, and resolve questions about training content.
• Participate in weekly meetings with clients to monitor progress, generate data quality reports, analyze performance trends, and recommend actionable improvements to ensure project alignment.