Jessie Branson

Key Skills

Software

Labelbox

CVAT

Other

Top Subject Matter

Machine Learning

AI Training & Quality Evaluation

Computer Vision

Top Data Types

Image

Text

Document

Top Task Types

Classification

Transcription

Freelancer Overview

Freelance Data Scientist & ML Engineer (Data Annotation & AI Training). Core strengths include Labelbox, CVAT, and Other. Education includes Bachelor of Science, University of Nairobi (2023). AI-training focus includes data types such as Image, Text, and Document and labeling workflows including Classification and Transcription.

Labeling Experience

Large-Scale Text & Audio Annotation Project (Freelance)

CVATTextTranscription

Curated, annotated, and transcribed text and audio data for large research and model training projects. Ensured consistency and accuracy by following strict annotation guidelines and conducting quality assurance checks. Produced both verbatim and clean-read transcripts on demand for various research clients. • Annotated interviews, lectures, and research documents at high volume. • Used Labelbox, CVAT, and Python-based platforms for bulk processing. • Maintained up-to-date annotation manuals and decision logs for the team. • Standardized output formats for seamless use in downstream analysis.

Curated, annotated, and transcribed text and audio data for large research and model training projects. Ensured consistency and accuracy by following strict annotation guidelines and conducting quality assurance checks. Produced both verbatim and clean-read transcripts on demand for various research clients. • Annotated interviews, lectures, and research documents at high volume. • Used Labelbox, CVAT, and Python-based platforms for bulk processing. • Maintained up-to-date annotation manuals and decision logs for the team. • Standardized output formats for seamless use in downstream analysis.

2020 - Present

Freelance Data Scientist & ML Engineer (Data Annotation & AI Training)

LabelboxImageClassification

Oversaw and executed the annotation and curation of image, text, and structured data for AI and ML projects. Used consistent labeling conventions and custom workflows to boost downstream model performance and reliability. Delivered rapid, high-quality annotated datasets on tight client deadlines. • Enhanced model accuracy by up to 25% through high-quality labeling. • Utilized Python, Labelbox, CVAT, and custom tools for annotation processes. • Streamlined workflows with automated preprocessing and validation scripts. • Maintained project documentation and facilitated clear client communication.

Oversaw and executed the annotation and curation of image, text, and structured data for AI and ML projects. Used consistent labeling conventions and custom workflows to boost downstream model performance and reliability. Delivered rapid, high-quality annotated datasets on tight client deadlines. • Enhanced model accuracy by up to 25% through high-quality labeling. • Utilized Python, Labelbox, CVAT, and custom tools for annotation processes. • Streamlined workflows with automated preprocessing and validation scripts. • Maintained project documentation and facilitated clear client communication.

2019 - Present

Dataset Cleaning, Labeling & Validation Workflow (Freelance)

OtherDocumentClassification

Designed workflows and conventions for cleaning, annotating, and validating diverse datasets, ensuring long-term usability. Reviewed and standardized documentation on annotation classes, formats, and quality controls. Provided continuous quality assurance and feedback to other annotators throughout projects. • Automated labeling pipelines using custom Python scripts. • Improved annotation consistency, reducing manual rework. • Created detailed documentation and process guides for team members. • Facilitated seamless handover to project stakeholders and clients.

Designed workflows and conventions for cleaning, annotating, and validating diverse datasets, ensuring long-term usability. Reviewed and standardized documentation on annotation classes, formats, and quality controls. Provided continuous quality assurance and feedback to other annotators throughout projects. • Automated labeling pipelines using custom Python scripts. • Improved annotation consistency, reducing manual rework. • Created detailed documentation and process guides for team members. • Facilitated seamless handover to project stakeholders and clients.

2021 - 2023

Education

Work History