I will do expert image labeling, data annotation, analysis, and visualization

Reliable, QA-checked data labeling for AI training from a Harvard researcher.

I label and annotate data the way research teams do it: against clear guidelines, with a second-pass quality check, and with a reported error rate so you know exactly what you're training on.

What I label:

Text classification & sentiment

Intent, topic & content moderation tagging

Named entity recognition (NER)

Image classification & tagging

Survey and open-ended response coding

LLM output rating & preference ranking

What you get:

Clean CSV or JSON, ready for your pipeline

Second-pass QA with blind re-check on a sample

Edge cases flagged, not silently guessed

Consistency and class-balance report

Inter-rater reliability metrics (Premium)

Why me: I build data pipelines in Python and R for research teams at Harvard Medical School, Columbia University and the University of Washington, including reliability and validation work across clinical scales. I know that bad labels don't just add noise they teach your model the wrong thing. Message me with a sample of your data and I'll tell you honestly whether I'm the right fit.