Featured Projects
Selected projects focused on predictive analytics, operational efficiency, and workflow improvement.
Predictive Modeling of Social Demographics & Birth Outcomes
Applied OLS, Poisson, and multinomial logistic regression to analyze and predict birth outcomes and demographic patterns.
Tools: Python, Statsmodels, Regression Analysis
View GitHub →Time Series Analysis & Model Refinement
Built linear and quadratic forecasting models and tested for serial correlation while improving model reliability using resampling techniques.
Tools: Python, Time Series, Statistical Testing
View GitHub →Sale Price Prediction Model
Developed a multiple linear regression model to predict housing sale prices while evaluating model significance and performance.
Tools: Python, Regression, Data Analysis
View GitHub →Logistic Regression Model
Built a classification model using thoracic surgery data to predict post-surgery survival outcomes.
Tools: Python, Classification, Data Preprocessing
View GitHub →Climate Data Analysis
Explored non-anthropogenic climate factors through statistical analysis of sunspot activity and magnetic data.
Tools: Statistical Analysis, Data Exploration
View GitHub →PDF Workflow Checker
Early-stage workflow validation system focused on reducing manual review errors and improving operational processing efficiency.
Status: In Development
Core Focus Areas
Data Analytics
Exploratory analysis, forecasting, predictive modeling, and business intelligence solutions.
Workflow Optimization
Identifying inefficiencies, reducing operational friction, and improving process efficiency.
Automation & Reporting
Building tools and workflows that reduce repetitive manual work and improve information visibility.
About
Reuben Decker LLC focuses on data systems, workflow optimization, operational analytics, and practical automation solutions.
Current work includes predictive modeling, time series analysis, workflow simplification, and operational intelligence projects designed to improve efficiency and decision-making.
Contact
Email: reubendecker@gmail.com
LinkedIn: linkedin.com/in/reubendecker-data
GitHub: github.com/dreubend