Tasik

Detail-oriented Data Annotation specialist with 97% accuracy maintaining high-volume labeling (100+ tasks/shift). Expert in pattern recognition, anomaly detection, and quality assurance. Proven ability to identify inefficiencies and implement systematic improvements resulting in 80% error reduction.

AI Analyst and Data Annotator (Part-Time) at RWS (2026-04 – Present)

• Annotate high-volume datasets with 97% accuracy across 100+ tasks/shift, adhering to detailed guidelines and SLAs in fast-paced environment
• Detect data inconsistencies and anomalies; apply independent judgment to resolve edge cases and ensure data integrity
• Identified systemic inefficiencies and automated 80% of validation checks, improving team productivity across 15+ evaluation cycles
• Document and escalate challenging cases per SOPs; collaborate with quality teams to establish consistent labeling standards

B.Tech in Electrical Engineering – B.P. Poddar Institute of Management and Technology (2019 – 2022)