Predictive Modeler Resume Schaumburg, IL - Hire IT People

SUMMARY

A challenging position as a statistician in which me can fully utilize my statistical knowledge and develop the professional skills dat me has acquired in my ten years statistical modeling in banking, commercial line insurance and real estate market
In - depth knowledge of probability, statistics, econometrics, Basel II risk parameters estimation and model validation including PD, LGD and EAD.
Extensive software knowledge: SAS, R, SPLUS, SPSS, SQL, EVIEWS, Minitab.
Remarkable data extracting & sampling, exploratory data analysis, data mining, and predictive modeling skills including GLM(Logistic Regression & Poisson Regression), ARIMA,VAR, GARCH, HLM, HGLM, Cox PH & AFT models, MCMC, Monte Carlo Simulation, PCA, Factor Analysis, Clustering, Decision Tree, Gradient Boosting, Neural Network and SVM.
Hands-on project experiences on logistic regression, Decision Tree, Gradient Boosting, time series analysis, panel data analysis, survival analysis, factor analysis, multilevel analysis multivariate analysis;
Effective time management and excellent interpersonal skills.

PROFESSIONAL EXPERIENCE

Confidential, Schaumburg, IL

Predictive Modeler

Responsibilities:

Perform data acquisition, manipulation, and cleansing for various external data sources for different lines of business.
Develop statistical modeling for various areas and purposes including Underwriting, Pricing, Claims, Marketing and Prospecting.
Analyze business prospect and research appropriate multivariate modeling techniques (e.g. GLM, linear regression, Clustering, Decision Tree, and Gradient Boosting etc.).
Support the model implementation process.

Confidential, Omaha, NE

Statistical Analyst

Responsibilities:

Develop, validate and test scorecards/segmentation models: 1)Redevelop acquisition response score for preapproved national marketing campaign with different targets to lending customers and spending customers; 2)Validate daily risk score for new booked accounts and provide redevelopment and credit line management recommendations; 3)Validate profit score to examine customer/business units migrations for consumer and commercial credit cards ; 4)Develop response channel model to assemble web responders profile and recommend cost effective marketing strategy etc.

Confidential, Chicago, IL

Teaching Assistant

Responsibilities:

Assisted the teaching of Applied Regression including non linear models, time series models, logistic models, and Poisson models.
Independent project of survival analysis on the risk of death due to Lymphoma
Analyzed survey data sets of health/disease by using hierarchical logistical models.
Led projects on multilevel analysis and multivariate analysis.
Established Sampling methodology and constructed Housing price index.
Used hedonic pricing models, time-series cross-sectional models ( for panel data) to analyze and predict housing market, assisted in housing policy making including real estate market regulation and low income housing policy.
Wrote the Monthly/Seasonal/Annual Real Estate Market Analysis for the Director ofthe Bureau to report at the Shanghai Mayor Meeting.
Created the Framework of Real Estate Market Monitoring System.