About Me
I am an end-to-end Data Scientist with a versatile skill set that spans statistical analysis, data modeling, machine learning, and modern data engineering. I am passionate about working across the full data lifecycle: from ingestion and transformation to modeling, deployment, and insight.
My work is driven by a passion for uncovering patterns in complex data and building systems that scale. While I continue to deepen my skills in data infrastructure and engineering, I remain committed to asking and answering novel questions through advanced data mining techniques.
To learn more about me or get in touch, please contact me through email or connect with me on LinkedIn.
Programming Languages
Skills and Interests
Current Strengths
Inferential Statistical Modeling: bivariate and multivariate ANOVA and Regression (linear and logistic)
Tree-Based Models: Decision Trees and Random Forest Models (Examples)
Dimensionality Reduction: Principal Component Analysis (PCA; Examples)
Web Scraping: BeautifulSoup and Selenium in Python (Examples)
Market Basket Analysis: Support, Confidence, and Lift (Examples)
Data Visualization and Reporting: Power BI and Tableau dashboards (Examples)
Actively Developing
Building advanced ETL workflows using APIs and Python scripting
Integrating disparate data sources into analyzable, well-structured formats
Designing scalable, relational database models using SQL
Engineering features from complex datasets to model nuanced constructs
Characterizing and predicting real-world decision-making behaviors