Samson Griffin

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CVAT

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Freelancer Overview

I am a highly motivated molecular biologist with deep experience in laboratory data analysis, experimental design, and scientific. documentation. My background includes advanced molecular assay development, DNA/RNA extraction, PCR, qPCR, and extensive work with complex biological datasets. I have supervised and trained junior researchers in accurate data collection, annotation, and interpretation, ensuring high-quality and reproducible results. My experience preparing data for publication and peer review has given me a meticulous eye for detail and accuracy, which I am eager to apply to data labeling and AI training data roles, especially in the domains of molecular diagnostics and medical research. I am skilled in handling large volumes of laboratory data, maintaining precise records, and adhering to rigorous quality standards. I have done data labeling and annotation before for machine learning in a biology project that required molecular biology knowledge I also did data annotation in the same setup for telus international.

Labeling Experience

Data annotator

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I labeled data for AI training within a healthcare setting, applying my background in molecular biology to accurately annotate clinical and laboratory datasets. I worked with genomic sequences, PCR results, microbiology reports, and other diagnostic data, ensuring each entry was correctly classified according to established biomedical standards and protocols. I carefully identified biomarkers, microbial species, and clinically significant patterns to support the development of AI models used in disease diagnosis and predictive healthcare analytics. Throughout the process, I maintained high levels of accuracy, consistency, and adherence to quality management and ethical guidelines to ensure reliable AI model performance.

I labeled data for AI training within a healthcare setting, applying my background in molecular biology to accurately annotate clinical and laboratory datasets. I worked with genomic sequences, PCR results, microbiology reports, and other diagnostic data, ensuring each entry was correctly classified according to established biomedical standards and protocols. I carefully identified biomarkers, microbial species, and clinically significant patterns to support the development of AI models used in disease diagnosis and predictive healthcare analytics. Throughout the process, I maintained high levels of accuracy, consistency, and adherence to quality management and ethical guidelines to ensure reliable AI model performance.

2022 - 2023

Education

Work History