- With extensive experience in development and deployment of quantitative models to drive insights into customer behavior, pricing trends, and medical outcomes
- I build successful strategies that increase Revenue by $2 million annually.
- With a degree in Economics, and 5+ years work in Data Science, I bring a combination of Industry Experience, and technical know - how.
- Created model that linked Macroeconomic Trends to the Real Estate market. Tested modeling paradigms including Panel Modeling, Difference in Difference, Granger Causality, and Time Series to find a method that produced results that could drive business decisions.
- Performed Data Science to support Machine Learning Algorithm on training data set with 10+ million observations. Quantified outliers that would impair model performance, noting variations that could endanger the model validity.
- Explored alternative modeling methodologies before recommending an XG Boosted model.
- Led financial forecasting and enabled strategic planning for a cardiac and pulmonary practice with more than 10,000 patient visits per year in a Metropolitan Statistical Area (MSA) of 6.9 million by developing a predictive linear model of third-party payment (TPP) with an R squared of 88% (accurate within $1.17 per insurance claim) across 56 health plans.
- Predictive Analytics
- Statistical Modeling
- Data Analysis
- Created financial econometric model that saved client $200,000 annually by improving the accuracy of the model
- Quantified risk of default for consumer loans, demonstrating how to save 2% in returns on portfolios of loans over with $1.3 million under management annually
- Created Real Estate Time Series model that included Micro Economic trends, increasing Revenue by 0.5% on portfolios with $5 million under management annually
- Created iterative Time Series Model to process 1500+ forecasts, improving budget projections by 12%
- Utilized Time Series modeling to understand gaps in Customer Satisfaction scores, resulting in 2% improvement to scores over 6-month time period
- Improved time-in-clinic metrics by more than 37% in less than three (3) months by analyzing survey results and generating actionable insights for leadership decision making.
- Developed actionable insight that drove business strategies, optimizing the model for individual centers resulting in opportunity to save $2 million annually
- Utilized multi-linear regression to analyze passenger surveys resulting in new understanding of primary drivers of satisfaction.
- Developed strategy to improve savings for Confidential Corp in their travel spend, saving $1 mil annually
- Analyzed Upgrade program offered by Airline, and recommended course of action