Health Data Scientist, MSc
I develop statistical pipelines and machine learning methods for large-scale biomedical data, from neuroimaging studies to national public health systems. My work finds meaningful patterns in high-dimensional, noisy biological data.
- Computational Neuroscience - Brain connectivity, neuropsychiatric disorders, reward processing
- Biomedical Data Science - Health surveillance, epidemiological modeling, clinical data systems
- Statistical Genomics - Variant analysis, multi-omic integration, disease mechanisms
- Research Equity - Open science, community-engaged research, capacity building
Languages: Python • R • SQL • HTML/CSS • JavaScript
Data & ML: pandas • NumPy • scikit-learn • PySpark • tidyr • caret • random forest • ensembles • OpenAI API
Cloud Platforms: Databricks • Snowflake • Azure • Power BI • Git
Methods: Statistical Modeling • Machine Learning • Network Analysis • Data Engineering • LLMs & NLP
Open Science Neuro Hackathon - Research tools for neuroscientists across the African diaspora
Neurodegenerative Genetics Pipeline - Variant analysis for Alzheimer's, Parkinson's, and related diseases
Predicting Self-Reported Substance Use - Ensemble regression model for predicting self-reported drug use
Khan Academy User Retention Analysis - Cohort retention analysis examining month 1 behavioral patterns and month 3 retention for 7,612 Khan Academy users
victoriamccray.github.io • LinkedIn • victoriapmccray@gmail.com
Open to opportunities in bioinformatics, computational neuroscience, and health data science!