Master of Science, Data Science
Eastern University · 2025
Chemistry + Quality + Data Science
I’m Zaida Bryce, a Florida-based quality data analyst and chemist who connects laboratory science, statistical thinking, and regulatory rigor.
A multidisciplinary perspective
My work lives where laboratory operations, data integrity, and analytical decision-making meet.
With a foundation in chemistry and advanced training in data science, I bring scientific discipline to data analysis and a systems mindset to quality assurance. I translate complex laboratory workflows into clear metrics, reliable documentation, and practical insights for technical and cross-functional teams.
Eastern University · 2025
University of South Florida
Core competencies
Python, R, SQL, regression, classification, NLP, clustering, time series forecasting, and hypothesis testing.
Clear analytical stories and interactive dashboards designed around meaningful KPIs and real user needs.
Data quality assurance, audits, CAPA, computerized system validation, and regulated laboratory practices.
Hands-on work across database, cloud, notebook, laboratory, and business productivity environments.
Professional experience
Florida Department of Agriculture and Consumer Services
Analyze laboratory and quality-control data to surface trends, anomalies, and compliance risks across regulated petroleum and metrology operations.
Eastern University
Helped students turn varied datasets into accurate, interactive, and audience-centered Tableau experiences.
Recovery Center of America / Genetworx & Dundy County Hospital
Produced reliable diagnostic data in CAP- and CLIA-regulated environments, connecting precise laboratory work with timely clinical decisions.
Applied data science
Academic projects spanning public health, computer vision, and predictive classification.
Public Health Analytics
Built ETL pipelines for more than 800,000 rows and used regression and correlation analysis to evaluate predictors of health outcomes.
Computer Vision
Implemented convolutional neural networks for image recognition and improved model accuracy through hyperparameter tuning.
Predictive Classification
Applied principal component analysis and classification models to distinguish edible mushrooms from poisonous ones.
Let’s connect
Interested in quality analytics, laboratory data systems, or data science work? I’d be glad to hear from you.
brycezf@gmail.com