I’m Phil Mumba, a detail-oriented NLP Data Annotator with 3+ years of experience labeling, classifying, and evaluating large-scale text datasets for AI and LLM systems. I specialize in sentiment labeling, intent classification, entity tagging, and text categorization across multilingual data, and I enjoy turning complex datasets into clean, reliable training material.
I work closely with cross-functional teams to maintain annotation guidelines, ensure quality and consistency, and push improvements in model performance through rigorous QA and iterative feedback. Fluent in Kiswahili and English, I support chatbots, search, and language-understanding models with clear communication and a friendly, collaborative approach.
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