Data Annotation
I was assigned to an image classification project where I was responsible for labeling large datasets. My daily task involved analyzing visual data and categorizing it according to a strict 50-item taxonomy. Beyond just clicking labels, I acted as the first line of quality control. I identified patterns where the model might struggle—such as low-light conditions or overlapping objects—and provided feedback to the data science team to refine the labeling guidelines. This resulted in a cleaner dataset, which directly led to higher model validation scores during the testing phase.