Lidon Mayors

Key Skills

Software

Label Studio

CVAT

Prodigy

Doccano

Top Subject Matter

Healthcare Data & Medical Documentation

Biotech Domain Expertise

Financial Compliance & Risk Analysis

Top Data Types

Image

Document

Text

Top Task Types

Segmentation

Classification

Entity (NER) Classification

Freelancer Overview

Director of Data Science & Annotation Strategy. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, CVAT, and Prodigy. Education includes Master of Science, University of Washington (2016) and Bachelor of Science, University of Washington (2014). AI-training focus includes data types such as Image, Document, and Text and labeling workflows including Segmentation, Classification, and Entity (NER) Classification.

Labeling Experience

Director of Data Science & Annotation Strategy

Label StudioImageSegmentation

As Director of Data Science & Annotation Strategy at NextGen AI Analytics, I led enterprise-wide annotation and labeling initiatives across multiple industries. My focus was on developing predictive models, QA rubrics, and automation to enhance efficiency and precision. This resulted in significantly higher data integrity and cycle time reduction. • Managed ISO-compliant annotation programs in healthcare, biotech, and finance • Designed QA frameworks delivering 99% accuracy in labeling • Automated annotation workflows to reduce cycle times by 45% • Coordinated cross-functional annotation teams

As Director of Data Science & Annotation Strategy at NextGen AI Analytics, I led enterprise-wide annotation and labeling initiatives across multiple industries. My focus was on developing predictive models, QA rubrics, and automation to enhance efficiency and precision. This resulted in significantly higher data integrity and cycle time reduction. • Managed ISO-compliant annotation programs in healthcare, biotech, and finance • Designed QA frameworks delivering 99% accuracy in labeling • Automated annotation workflows to reduce cycle times by 45% • Coordinated cross-functional annotation teams

2026 - Present

Biotech R&D Director

CVATImageSegmentation

As Biotech R&D Director at Seattle Genetics Inc., I integrated automated annotation and data science workflows for biomedical research. My innovations led to substantial improvements in model accuracy and annotation process efficiency. I built annotation pipelines using Python and Spark to optimize large-scale datasets. • Automated annotation pipelines by 40% reduction of manual work • Improved AI model accuracy by 25% through precise labeling • Leveraged data science methods for annotation consistency • Oversaw large biomedical labeling initiatives

As Biotech R&D Director at Seattle Genetics Inc., I integrated automated annotation and data science workflows for biomedical research. My innovations led to substantial improvements in model accuracy and annotation process efficiency. I built annotation pipelines using Python and Spark to optimize large-scale datasets. • Automated annotation pipelines by 40% reduction of manual work • Improved AI model accuracy by 25% through precise labeling • Leveraged data science methods for annotation consistency • Oversaw large biomedical labeling initiatives

2021 - 2026

Senior Annotation & Data Science Lead

ProdigyDocumentClassification

As Senior Annotation & Data Science Lead at Data Annotation Solutions, I directed a team specializing in biomedical dataset annotation. My role included developing and refining validation models and reproducibility testing frameworks. We systematically improved annotation accuracy and reproducibility for sensitive biomedical projects. • Supervised a 25-person annotation team for complex datasets • Created QA protocols resulting in 35% more consistent annotations • Used scripting for bias detection and rubric development • Led reproducibility and compliance-driven annotation testing

As Senior Annotation & Data Science Lead at Data Annotation Solutions, I directed a team specializing in biomedical dataset annotation. My role included developing and refining validation models and reproducibility testing frameworks. We systematically improved annotation accuracy and reproducibility for sensitive biomedical projects. • Supervised a 25-person annotation team for complex datasets • Created QA protocols resulting in 35% more consistent annotations • Used scripting for bias detection and rubric development • Led reproducibility and compliance-driven annotation testing

2017 - 2021

Data Science Analyst & Workflow Engineer

DoccanoTextEntity Ner Classification

At Pacific Northwest Data Labs, I worked as a Data Science Analyst & Workflow Engineer developing ETL pipelines and QA metrics for annotation tracking. I established robust annotation validation systems and designed dashboards to monitor progress and quality. The role involved building and testing annotation workflow automation for healthcare NLP projects. • Built ETL and annotation progress tracking systems • Devised dashboards to monitor annotation and QA metrics • Developed automated annotation quality checks • Supported annotation workflow optimization for NLP

At Pacific Northwest Data Labs, I worked as a Data Science Analyst & Workflow Engineer developing ETL pipelines and QA metrics for annotation tracking. I established robust annotation validation systems and designed dashboards to monitor progress and quality. The role involved building and testing annotation workflow automation for healthcare NLP projects. • Built ETL and annotation progress tracking systems • Devised dashboards to monitor annotation and QA metrics • Developed automated annotation quality checks • Supported annotation workflow optimization for NLP

2015 - 2017

Data Visualization Specialist

Label StudioImage

I was a Data Visualization Specialist at Evergreen Analytics, focusing on annotation performance monitoring systems. My main contributions were building Power BI dashboards and delivering insights to guide annotation and labeling improvement. This work helped optimize enterprise labeling workflows for large-scale projects. • Developed annotation performance dashboards using Power BI • Provided statistical feedback to improve labeling workflows • Tracked and evaluated labeling and annotation progress • Assisted in performance monitoring across labeling projects

I was a Data Visualization Specialist at Evergreen Analytics, focusing on annotation performance monitoring systems. My main contributions were building Power BI dashboards and delivering insights to guide annotation and labeling improvement. This work helped optimize enterprise labeling workflows for large-scale projects. • Developed annotation performance dashboards using Power BI • Provided statistical feedback to improve labeling workflows • Tracked and evaluated labeling and annotation progress • Assisted in performance monitoring across labeling projects

2013 - 2015

Education

Work History