Text Classification & Annotation for Customer Support Data
TextClassification
Worked on classifying and labeling large volumes of customer support data by categorizing user queries into predefined labels such as billing, technical issues, onboarding, and account-related concerns. Processed an average of 60–100 data points daily, ensuring consistency and accuracy across all annotations.
Applied structured guidelines to maintain uniform labeling standards and improve data usability for downstream processes such as analytics and content development. Regularly reviewed labeled data to identify inconsistencies and ensure high-quality outputs.
Worked on classifying and labeling large volumes of customer support data by categorizing user queries into predefined labels such as billing, technical issues, onboarding, and account-related concerns. Processed an average of 60–100 data points daily, ensuring consistency and accuracy across all annotations. Applied structured guidelines to maintain uniform labeling standards and improve data usability for downstream processes such as analytics and content development. Regularly reviewed labeled data to identify inconsistencies and ensure high-quality outputs.
2024 - 2026