Key Skills

Software

Humanatic

Labelbox

Label Studio

SuperAnnotate

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Geospatial Tiled Imagery

Image

Top Task Types

Action Recognition

Audio Recording

Classification

Emotion Recognition

Translation Localization

Freelancer Overview

With over three years of specialized experience in data labeling and AI training data, I have developed and executed annotation frameworks across computer vision, natural language processing, and medical imaging domains. I design rigorous annotation taxonomies and comprehensive guidelines to ensure consistent, high‑fidelity labels—whether segmenting anatomical structures in CT scans using VIA, bounding and classifying e‑commerce product images in Labelbox, or annotating customer support transcripts for intent and sentiment in Label Studio. My technical toolkit includes mastery of SuperAnnotate, Prodigy, doccano, and Roboflow, as well as bespoke Python scripts for data transformation, format conversion, and API integration. These capabilities enable me to streamline annotation workflows, achieve inter‑annotator agreement rates above 90%, and deliver training datasets that consistently improve downstream model performance. In addition to hands‑on annotation, I have led quality assurance initiatives and cross‑functional collaboration with machine learning engineers and domain experts. I establish clear QA protocols, monitor key metrics, and refine taxonomies to reduce relabel cycles by up to 30%. Noteworthy projects include the creation of a 15,000‑post social‑media sentiment corpus, the development of standard operating procedures for CT‑slice segmentation in partnership with radiologists, and the deployment of object‑detection pipelines that decreased setup time by 40%. Armed

Labeling Experience

Education

Work History