Dallas, Texas, United States
I am a behavioral modeler with experience in fixed incomes and strong familiarity with R, SQL, Google BigQuery, Amazon Redshift, statistical data analysis, and various modeling techniques. I have a strong passion for statistics and creativity and utilizing these techniques in the financial world to develop new solutions to problems which are both accurate and efficient. I have a Yale Economics BA with a focus in statistics and developmental macroeconomics.
Build loan level mortgage prepayment, credit, and timeline models across Agency, FHA, VA, Non-QM, Jumbo and other sectors for Whole Loan and MSR valuation, hedging, brokerage, and more. Lead research efforts on changing market trends, the real-estate landscape (E.G. climate, Home prices, ect) and data product development Client interaction RE: modeling and analytics as well as conference speaking roles.
Prepayment, credit, and loss modeling across Conventional, GNMA, and non-agency (legacy, non- QM and Jumbo) collateral. Data product development that ranges from MSR brokerage to TBA attribute estimation.
I build and maintain prepay, credit, and severity models for loans in agency, government, and private label securities. I have my hands on every part of the process, from the data sampling, variable creation, exploratory research, estimation, and implementation for the models. I can handle corner cases such as pass-through models, non-performing loans, non-QM, and so on. The models are used by government agencies, hedge funds, bond rating agencies, and other large institutions involved in fixed incomes
Helped with the historical data production for MIAC's extensive loan-level databases. Trained in the use of SQL and various MIAC products for this specific purpose. Assisted in the creation of data loading models for over 10 different projects in my 3 months
Used regression modeling to determine ROI for the dealership's advertising, helping to increase efficiency of spend, and increase traffic to the dealership. Also used data mining from the dealership's resources to create most of the data sets I used in these regressions. Did price elasticity studies using the entirety of new Volkswagens available in Denver to show where price could be increased without hurting demand Set up an Amazon marketplace with 200+ items, using formulas to price them competitively while still making a profit on every item. $30,000+ a month in sales within a year of creation