Tom Moore

Key Skills

Software

Label Studio

Sama

Remotasks

Scale AI

Top Subject Matter

Academic NLP research

low-resource African languages

Content moderation

Top Data Types

Text

Image

Document

Top Task Types

Entity Ner Classification

Classification

Object Detection

Freelancer Overview

Research Assistant (Data & Documentation). Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Label Studio, Sama, and Remotasks. Education includes Bachelor of Science, University of South California (2019). AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification, Classification, and Object Detection.

Labeling Experience

Freelance AI Data Annotation Specialist (Text)

Scale AITextEntity Ner Classification

I performed NER tagging and sentiment labeling on multilingual text corpora to support NLP model improvement. I contributed structured annotations that enhanced model capabilities across multiple languages. I reviewed and validated peer annotations to reduce errors and elevate dataset quality. • Labeled text datasets using NER and sentiment analysis techniques. • Contributed to NLP pipelines for five language sets, supporting AI training. • Maintained high labeling accuracy through adherence to project taxonomy. • Participated in quality assurance cycles and cross-team milestone reviews.

I performed NER tagging and sentiment labeling on multilingual text corpora to support NLP model improvement. I contributed structured annotations that enhanced model capabilities across multiple languages. I reviewed and validated peer annotations to reduce errors and elevate dataset quality. • Labeled text datasets using NER and sentiment analysis techniques. • Contributed to NLP pipelines for five language sets, supporting AI training. • Maintained high labeling accuracy through adherence to project taxonomy. • Participated in quality assurance cycles and cross-team milestone reviews.

2022 - Present

Freelance AI Data Annotation Specialist (Images)

RemotasksImageObject Detection

I annotated and labeled high volumes of images for computer vision projects, focusing on object detection and segmentation tasks. I ensured accuracy in tagging for models used in autonomous vehicle and healthcare AI applications. I collaborated with a distributed team and participated in regular QA cycles to maintain dataset quality. • Managed image annotation for large-scale datasets with a 98.6% accuracy rate. • Supported labeling for object detection, segmentation, and computer vision workflows. • Used established annotation pipelines to meet weekly project milestones. • Reduced error rates by conducting regular reviews of peer annotations.

I annotated and labeled high volumes of images for computer vision projects, focusing on object detection and segmentation tasks. I ensured accuracy in tagging for models used in autonomous vehicle and healthcare AI applications. I collaborated with a distributed team and participated in regular QA cycles to maintain dataset quality. • Managed image annotation for large-scale datasets with a 98.6% accuracy rate. • Supported labeling for object detection, segmentation, and computer vision workflows. • Used established annotation pipelines to meet weekly project milestones. • Reduced error rates by conducting regular reviews of peer annotations.

2022 - Present

Content Reviewer & Quality Analyst

SamaTextClassification

I reviewed and categorized large volumes of user-generated content using detailed classification taxonomies, achieving high-accuracy annotation outputs. I provided structured feedback and contributed to revisions of annotation guidelines to improve team consistency. I mentored junior annotators on best labeling practices and standards. • Reviewed over 80,000 content items each month for structured labeling. • Collaborated with international project leads to resolve ambiguous annotations. • Played a key role in improving taxonomy clarity and labeling consistency. • Reduced onboarding time for new team members by 30% through training efforts.

I reviewed and categorized large volumes of user-generated content using detailed classification taxonomies, achieving high-accuracy annotation outputs. I provided structured feedback and contributed to revisions of annotation guidelines to improve team consistency. I mentored junior annotators on best labeling practices and standards. • Reviewed over 80,000 content items each month for structured labeling. • Collaborated with international project leads to resolve ambiguous annotations. • Played a key role in improving taxonomy clarity and labeling consistency. • Reduced onboarding time for new team members by 30% through training efforts.

2020 - 2021

Research Assistant (Data & Documentation)

Label StudioTextEntity Ner Classification

I supported faculty research by collecting, organizing, and labeling structured datasets used for NLP studies on low-resource African languages. I applied consistent metadata tagging across 6,000+ research documents to enhance searchability and readiness for AI training. I managed data quality control and coordinated student volunteers to maintain annotation standards. • Built a structured document repository for research and AI pipeline use. • Conducted NER labeling and classification on text data for NLP projects. • Ensured dataset consistency by adhering to predefined annotation standards. • Assisted in coordinating data drives involving over 200 student contributors.

I supported faculty research by collecting, organizing, and labeling structured datasets used for NLP studies on low-resource African languages. I applied consistent metadata tagging across 6,000+ research documents to enhance searchability and readiness for AI training. I managed data quality control and coordinated student volunteers to maintain annotation standards. • Built a structured document repository for research and AI pipeline use. • Conducted NER labeling and classification on text data for NLP projects. • Ensured dataset consistency by adhering to predefined annotation standards. • Assisted in coordinating data drives involving over 200 student contributors.

2019 - 2020

Education

Work History