Design, develop, and refine TFS (macroeconomic) forecasting models that are fully integrated with Residual Risk and lease portfolio analysis.
Use econometric modeling and appropriate statistical techniques to identify factors that correlate with severity and frequency metrics. These factors include used vehicle values and the probability of lease vehicles returning at lease end.
Combine mathematical relationships into a semi-automated model that forecasts metrics listed above and is used as a decision support tool.
Develop, leverage, and enhance internal portfolio data and external data sources (i.e., Toyota/ AuctionNet, Global Insight, Moody's Economy.com, etc.) used in analysis and forecasting
Collect, and analyze auto industry and economic information and data impacting used vehicle prices, including, but not limited to, information regarding economic trends/forecasts, new and used car markets, emerging technology, and competitor vehicles and sales
Use the latest analytical tools to programmically extract, clean, and analyze large, disparate, disorderly data sets
- Master’s in Statistics, Economics or other math-related degree, or an MBA
- Experience in a strategy and statistical model development role
- Familiarity with or business use of alternative analytical tools, such as: R, JMP, Python (Numpy/Pandas), scikit-learn, CART, Stata, TreeNet, Angoss KnowledgeStudio, Apache Hadoop
- Proficient in various statistical techniques, such as: Logistic Regression, Time Series, Experimental Design, Generalized Linear Models, Mixed Modeling, Multivariate Statistics, Large-Scale Predictive Modeling, CHAID/decision trees, Neural Networks, Monte-Carlo, Survival Analysis, Ensemble Models