Model Implementation/Data Analyst Resume McLean, VA - Hire IT People

SUMMARY:

Strong quantitative, programming and analytical skills. Proficient in Statistical analysis, Predictive Modeling, Credit Risk Analysis and statistical programming.
Excellent written and verbal communications skills. Team facilitator; willingness to learn.
Risk Management, Credit Card Fraud, Basel - 2, Database Marketing, Segmentation & Clustering, Linear and Logistic Regression, Time Series Analysis, Multivariate Analysis-Principal Component, Factor Analysis Discriminant Analysis, SAS/SPSS/PASW/STATA, SAS Enterprise Guide, R, SQL, Teradata, VBA, KXEN, Data Mining, Test/Control Design, Survey, Data Preparation, Model Building and Validation, Application Development in UNIX and Shell Scripting, Scenario Analysis and Stress Testing

COMPUTER SKILLS:

Statistical Software: SAS 9.1 - DATA Step, BASE SAS, PROC SQL, SAS/STAT, SAS IML, SAS ETS, SAS Macro Programming, SAS Enterprise Miner, SPSS, PASW, STATA, R, Win-bugs, KXEN, CHAID

Applications: Word, PowerPoint, Excel- Pivot Tables VLOOKUP Index VBA, MATLAB (Numerical Analysis), UNIX Scripting Optimization- Excel Solver, AMPL Simulation- Arena 10.0

Languages: C, C++, SQL.

Database: Oracle, MS Access, MS SQL Server 2005, PostGRESQL, SAS/SQL

Mainframe: MVS, JCL, COBOL, CICS, DB2

WORK EXPERIENCE:

Model Implementation/Data Analyst

Confidential, McLean, VA

Responsibilities:

Writing, maintaining and implementing credit models in SAS for Mortgage and Auto Loans
BASEL 2 PD, LGD, EAD segmentation, RWA calculation and model implementation for Mortgage portfolio
Loan Loss Forecasting for Mortgage Portfolio; calculating accounting and economic losses
Model Validation using SAS/STAT; model documentation and writing white papers
Coding in SAS Enterprise Guide and SAS Macros for model implementation

SAS Systems Developer

Confidential, Columbus, OH

Responsibilities:

Develop SAS Macros for Anti Money Laundering services; Analytics using SAS, SAS Macros, SAS SQL
Modifying existing scenarios and creating new scenarios for AML/BSA

Lead Analyst

Confidential, Hoffman Estates, IL

Responsibilities:

Develop propensity models for targeting customers.
Writing queries in Teradata for complex ad-hoc business analysis

Confidential, Downers Grove, IL

SAS Consultant

Responsibilities:

PD Modeling by regression methodology using mortgage loan specific characteristics like LTV, FICO and macroeconomic variables
Using multivariate statistical methods, data mining and econometric methods for segmentation, credit risk modeling, regression analysis, forecasting and Stress Testing
SAS ODS reporting and generating monthly reports (Asset Liability Management, Performance Analysis)

Confidential, Naperville IL

Sr Consultant

Responsibilities:

Automating retail and contract pricing using SAS. Data Mining and Data Preparation. Report automation using Excel and SAS

Confidential, Phoenix, AZ

Manager (Risk Management)

Responsibilities:

Credit card fraud mitigation strategies to enhance profitability.
Generating reports in SAS Enterprise Guide. Creating views and tables using PROC SQL and Teradata
Modified statistical models to calculate ProbF and Lift- probability measures to calculate fraud risk of a transaction

Confidential, Schaumburg, IL

Sr. Statistical Analyst (Marketing Analytics)

Responsibilities:

Coupon redemption by Smartphone customer analysis with retail data using SAS, Logistic Regression, Optimization- Linear and Integer, Kernel Density Estimation. Correlation/Covariance Analysis
Reporting ad hoc SQL query metrics using Teradata to client.

Confidential, Mettawa, IL

Sr. Credit Policy/ Risk Analyst

Responsibilities:

Estimation and validation of risk parameters - Probability of Default (PD), Exposure At Default (EAD) and Loss Given Default (LGD) for Basel II regulatory compliance.
Created and maintained econometric models that forecasted the levels, percentages, and/or characteristics of commercial loans for risk management and Stress Testing purposes.
E Developed clustering model using K-means with internal and bureau variables to identify risky pockets of population as an alternative to segmentation modeling using SAS, R

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Model Implementation/data Analyst Resume

Mclean, VA

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