Brian Weiss
A decade of experience helping organizations get more value from their data, increasing quality of output and reducing costs of maintenance. I build data systems that turn manual work into governed automation, capable of turning multiple inputs into trusted analysis and actionable insights: performance dashboards, evaluation models, and executive narratives to drive funding and strategy decisions. I have done this across enterprise finance, pharmaceutical marketing, and high-visibility philanthropy, each with its own compliance structure and stakeholder complexity.
Python · R · SQL · Tableau · dbt
Selected Work
Research & Strategy
COVID-19 and the Household Pulse Survey: Predicting Vaccine Intent and Developing Persona-driven Messaging
Analysis of U.S. Census Bureau Household Pulse Survey data to model vaccine hesitancy and develop targeted messaging frameworks. Combines predictive modeling with behavioral segmentation to support public health communication strategy.
Research & Data Analysis
Chronic Kidney Disease: Predictive Risk Modeling
Data analysis project examining chronic kidney disease indicators and outcomes. Applies statistical modeling to clinical features to surface insights relevant to diagnosis and risk assessment.
Machine Learning · Python
Housing Price Prediction: Modeling Residential Sale Prices
Linear regression model predicting residential sale prices on the Ames Housing dataset (~80 features). Covers feature selection, categorical encoding, missing data handling, train/test splitting, and model evaluation across MAE, MSE, and RMSE.
Data Visualization · Tableau
US Labor Market Pulse: Are Workers Still Scarce Relative to Job Openings?
Interactive dashboard tracking the ratio of job openings to available workers across U.S. labor markets, drawing on BLS data to surface tightness trends over time.
Data Visualization · Tableau
CRM Sales Pipeline: Are We Hitting Our Numbers?
Pipeline health dashboard built on CRM data, tracking deal stage conversion, forecast accuracy, and rep performance to give revenue leadership a single view of whether the quarter is on track.