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I'm Flagg Chelsea Marie, a senior data specialist focused on data annotation, evaluation, and quality assurance for Fortune 500 tech companies. I excel at building scalable annotation workflows, maintaining granular task-level accuracy, and aligning data processes with AI safety and fairness goals. I enjoy balancing leadership with hands-on execution, with extensive experience in pairwise comparisons, multimodal tagging, and compliance-driven data QA. I hold a Master's in Data Science and am seeking flexible, project-based roles where advanced expertise can directly enhance AI safety, fairness, and performance. With a passion for turning complex data into reliable AI systems, I bridge strategy and execution, lead cross-functional teams, and design rigorous rubrics and workflows that improve speed and quality. I’m eager to contribute to high-impact AI safety and performance initiatives in a flexible, project-based capacity.…I'm Flagg Chelsea Marie, a senior data specialist focused on data annotation, evaluation, and quality assurance for Fortune 500 tech companies. I excel at building scalable annotation workflows, maintaining granular task-level accuracy, and aligning data processes with AI safety and fairness goals. I enjoy balancing leadership with hands-on execution, with extensive experience in pairwise comparisons, multimodal tagging, and compliance-driven data QA. I hold a Master's in Data Science and am seeking flexible, project-based roles where advanced expertise can directly enhance AI safety, fairness, and performance. With a passion for turning complex data into reliable AI systems, I bridge strategy and execution, lead cross-functional teams, and design rigorous rubrics and workflows that improve speed and quality. I’m eager to contribute to high-impact AI safety and performance initiatives in a flexible, project-based capacity.

Flagg Chelsea Marie

Data Scientist, QA Engineer, AI Strategy Consultant, +2

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I'm Flagg Chelsea Marie, a senior data specialist focused on data annotation, evaluation, and quality assurance for Fortune 500 tech companies. I excel at building scalable annotation workflows, maintaining granular task-level accuracy, and aligning data processes with AI safety and fairness goals. I enjoy balancing leadership with hands-on execution, with extensive experience in pairwise comparisons, multimodal tagging, and compliance-driven data QA. I hold a Master's in Data Science and am seeking flexible, project-based roles where advanced expertise can directly enhance AI safety, fairness, and performance. With a passion for turning complex data into reliable AI systems, I bridge strategy and execution, lead cross-functional teams, and design rigorous rubrics and workflows that improve speed and quality. I’m eager to contribute to high-impact AI safety and performance initiatives in a flexible, project-based capacity.…I'm Flagg Chelsea Marie, a senior data specialist focused on data annotation, evaluation, and quality assurance for Fortune 500 tech companies. I excel at building scalable annotation workflows, maintaining granular task-level accuracy, and aligning data processes with AI safety and fairness goals. I enjoy balancing leadership with hands-on execution, with extensive experience in pairwise comparisons, multimodal tagging, and compliance-driven data QA. I hold a Master's in Data Science and am seeking flexible, project-based roles where advanced expertise can directly enhance AI safety, fairness, and performance. With a passion for turning complex data into reliable AI systems, I bridge strategy and execution, lead cross-functional teams, and design rigorous rubrics and workflows that improve speed and quality. I’m eager to contribute to high-impact AI safety and performance initiatives in a flexible, project-based capacity.

Available to hire

I’m Flagg Chelsea Marie, a senior data specialist focused on data annotation, evaluation, and quality assurance for Fortune 500 tech companies. I excel at building scalable annotation workflows, maintaining granular task-level accuracy, and aligning data processes with AI safety and fairness goals. I enjoy balancing leadership with hands-on execution, with extensive experience in pairwise comparisons, multimodal tagging, and compliance-driven data QA. I hold a Master’s in Data Science and am seeking flexible, project-based roles where advanced expertise can directly enhance AI safety, fairness, and performance.

With a passion for turning complex data into reliable AI systems, I bridge strategy and execution, lead cross-functional teams, and design rigorous rubrics and workflows that improve speed and quality. I’m eager to contribute to high-impact AI safety and performance initiatives in a flexible, project-based capacity.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Senior data operations manager (Hands-on contributor) at Google

January 1, 2019 - Present

Managed and actively contributed to multimodal data annotation projects (text, image, audio), directly completing annotation tasks alongside team members to ensure consistency. Standardized global annotation guidelines adopted across 5+ product teams; personally annotated 10,000+ data points to validate quality. Spearheaded a 500,000+ output pairwise evaluation project, developing a scoring framework that became the benchmark for LLM safety reviews. Improved annotation efficiency by 30% via workflow automation, reducing project timelines without sacrificing accuracy.

Data quality assurance lead (AI services) at Amazon Web Services (AWS)

January 1, 2015 - December 31, 2019

Built datasets of 1M+ annotated images and text samples for AWS AI platforms. Introduced task-level QA checkpoints; personally reviewed 20,000+ labeled samples to raise accuracy from 88% to 99.5%. Created step-by-step annotation training manuals and micro-guides, cutting onboarding time for new contributors by 50%.

Data analyst (Annotation specialist) at Apple

January 1, 2012 - December 31, 2015

Direct contributor to Siri’s Natural Language Understanding team: annotated and categorized tens of thousands of utterances to improve intent classification. Performed counting, categorization, and pairwise review tasks on large datasets to refine language model outputs. Collaborated closely with engineers to flag annotation inconsistencies and retrain models for higher precision.