Bio

I am a full-stack data scientist with experience across technologies, statistical methods, and validation. My natural curiosity and drive to find the best solution for the business problem has led me to teach myself multiple coding languages and techniques in addition to what I learned in my Masters and Ph.D. programs and at State Farm. I have strong relationships across the analytics community and serve as a resource for modeling techniques. -Programming language – SAS (advanced), R (advanced), Python (advanced), SQL (advanced), Java (basic), SPSS (basic) MatLab (basic), Stata (intermediate), AWS Services (intermediate), Bash (intermediate), experience with CI/CD pipelines, automated test, and containers -Experience assessing effectiveness of and building models using a broad array of techniques – from generalized linear models to machine learning approaches like random forests and neural networks. -Deep understanding of model validation process for financial services. This involves critical and independent thinking regarding the business problem, data, modeling methodologies, model implementation, and model performance. -Strong understanding of how models are implemented. Experience identifying errors in how models were implemented that resulted in materially different results.