Posted:1 week ago|
Platform:
Work from Office
Full Time
Key Responsibilities: Analyze large volumes of labeled and unlabeled data to identify trends, anomalies, and labeling patterns that can improve model training or operational efficiency. Design and maintain automated dashboards and reporting frameworks to track labeling quality, throughput, and issue trends. Partner with Client leadership to understand data requirements and provide actionable insights for model optimization. Develop scalable data pipelines for data validation, aggregation, and visualization. Apply data mining techniques to evaluate annotation consistency, inter-rater reliability, and data quality. Contribute to AI data evaluation strategies through analytical experimentation and feedback integration. Collaborate with cross-functional teams to enhance data annotation workflows and ensure metrics alignment. Requirements : Bachelors degree in Statistics, Mathematics, Computer Science, Data Science, or a related field. 3–8 years of hands-on experience in data analysis roles, preferably in AI/ML or data labeling environments. Proficient in SQL and Python for data manipulation, analysis, and automation. Understanding of data labeling workflows and familiarity with metrics like accuracy, precision, recall, and inter-rater agreement. Strong analytical thinking with the ability to interpret large datasets and provide actionable insights. Excellent communication skills with the ability to present findings to both technical and non-technical audiences. Self-starter with a keen eye for detail and a passion for working in AI-driven data environments.
Teleperformance (TP)
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