Sas Programmer

SUMMARY

PhD graduate with major courses in Economics /Ag. Economics, Statistics, and Accounting, and 15 years work experience in credit card acquisition/activation, financial and retail product marketing campaign, auto and mortgage loan default and prepayment prediction, customer segmentation, cash flow forecast for marketing campaign and auto loans, Fair Lending Analysis, Basel compliance, financial fraud, and clinical trials.

Developed predictive models used for marketing campaign targeting and customer retention. Scorecard models for mortgage loan approval. Competing risk churn models for proactive action. Statistical and econometric models in defending bank for fair lending charges by the Office of Thrift Supervision (OTS), and in demand elasticity estimation. Time series ARIMA models for cash flow forecast of auto/credit card loans. Probability of mortgage loan default models for CCAR/Basel compliance.

WORK EXPERIENCE

Wells Fargo, McLean, VA

09.2014 – 01.2015

Sr. Statistician

Under Wells Fargo’s Corporate Model Risk (CMoR) team, validated home mortgage retail credit loss models in compliance with The Federal Reserve’s Capital Plan Rule and the associated annual Comprehensive Capital Analysis and Review (CCAR).

Evaluated evidence in support of all model choices, including the overall theoretical construction, key assumptions, data, specific mathematical calculations, and consistency with published research and sound industry practice. Following the supervisory guidance on model risk management of the “Board of Governors of the Federal Reserve System Office of the Comptroller of the Currency (OCC)”.

Reviewed model concept, business requirement, model process, data source, and model implementation as well as SAS code of data process and model creation. Validated model data and replicated model results in various modeling stages.

Provided statistical data summary, charts, and analyses of home mortgage loans using SAS/Base, SAS/macro, SAS/SQL, SAS/EG, SAS/STAT, and SAS/EM to generate model test measures, such as back-testing, to assess the accuracy of estimates or forecasts, rank-ordering ability, or other appropriate tests on model sample.

Chico’s FAS, Fort Myers, FL

08.2013 – 08.2014

Sr. Statistician

Applied statistical methods of significance testing, sampling, experimental design, regression analysis, and cluster analysis to support the retail marketing’s analytical initiatives.

Prepared model development samples and other datasets for statistical modeling, and summary reports.

Developed logistic predictive models for marketing campaign targeting and customer retention for active and lapsed customers.

PNC Financial Services, Pittsburgh, PA

03.2012 – 08.2012

Sr. Statistical Analyst

Applied SAS to estimate profit and loss of consumer loans over the months of performance on book, such as components of revenues and expenses for calculating economic profit and loss measures at individual and portfolio level.

Automated the profit and loss and data abnormality reporting in UNIX platform, using Excel Pivot table and SAS macros.

ORBITTZ, Chicago, IL

06.2011 –11. 2011

Sr. Statistician

Applied statistical methods including significance testing, sampling, experimental design, regression analysis, and cluster analysis to support CRM’s statistical and analytical initiatives website and email marketing.

Developed customer segmentation using SAS cluster procedures for marketing loyalty program.

Developed customer life time value to support email marketing including probability and monetary value of purchase of next year.

Used SAS Enterprise Miner decision tree to model number of days before departure a customer will attach a hotel.

Bank of America, Charlotte, NC

08.2010 –05. 2011

Sr. Statistician

Validated statistical models used in credit card account acquisition, credit line assignment, mortgage insurance loss forecast, loan loss recovery, and probability of mortgage loan default (PD) and payoff.

Evaluated evidence in support of all model choices, including the overall theoretical construction, key assumptions, data, specific mathematical calculations, and consistency with published research and sound industry practice.

Reviewed model documents and program code in SAS and SQL. Validated model results by independently reproducing the model output.

Assessed the accuracy of estimates or forecasts, rank-ordering ability, or other appropriate tests on model sample.

Conducted back-testing for the comparison of actual outcomes with model forecasts during a sample time period not used in model development and at an observation frequency that matches the forecast horizon or performance window of the model.

Performed validation of models in UNIX environment.

J.P. Morgan Chase, Columbus, OH

03.2010 – 07.2010

Sr. Risk Analyst

Based on existing model framework, updated and implemented mortgage risk models to forecast probability of default (PD) for Basel II capital reserve, like how much capital banks need to put aside to guard against the types of financial and operational risks banks face based on estimates of loss given default (LGD), capital exposure at default (EAD), and risk weighted assets (RWA). Used SAS Enterprise Guide, SAS/Base, SAS/Macro, SAS/Stat, SAS/SQL.

Data Computer Corporation of America (DCCA), Ellicott City, MD

04.2008 –12. 2009

Sr. Principal Statistician

Managed and developed programs to automatically generate summary report of Medicaid drug utilization (large-scale pay for reporting program) across comparable quarters at national level.

Developed programs to generate Medicaid State Drug Utilization Top 50 Report run automatically upon request.

Conducted statistical analysis of the State Medicaid Drug Utilization to identify data abnormality. As result of the analysis, developed a screening scheme to detect possible data errors in quarterly state data. Developed SAS and SQL routines to automatically screen state tapes for potential errors before loading to the database.

Financial Industry Regulatory Authority FINRA, Rockville, MD

04.2007 – 03.2008

Risk Management Consultant

Provided statistics and SAS support, and conducted extensive analyses of rich data by using SAS, SAS/macro, SAS/SQL, SAS/EG, SAS/STAT, and SAS/EM to monitor and identify transactional fraud of Dow and NASDAG member firms, regulatory violations, and financial risk.

Wells Fargo, Frederick, MD

11.2005 – 03.2007

Risk Management Consultant

From scratch, developed mortgage scorecard model to assess applicants’ credit risk, such as probability of Default (PD), using “SAS Enterprise Miner” scorecard that is based on a number of characteristic inputs, each characteristic is comprised of a number of attributes.

Conducted statistical analysis such as ID Prime and Sub Prime loans in SAS/EM.

Pricewaterhousecoppers (PWC), Washington, DC

03.2005 – 10.2005

Sr. Associate

Assessed whether race or another prohibited basis is a significant factor in pricing or underwriting decisions in a factorial regression model framework, while controlling for other sources of variance such as credit scores, LTVs, and many other factors associated with the lending process.

Validated statistical and non-statistical models used for credit risk management, asset valuations, and accounting purposes. Such as Mortgage Prepayment, Default, loss forecast models for Freddie Mac, Countrywide, AmeriQuest, GMAC, UBS, and First National Bank.

Sprint / Nextel Inc., Atlanta, GA

04.2004 – 02.2005

Sr. Statistician

Developed predictive models such as churn, response, and up-sell & cross-sell models. This modeling process includes the evaluation of needs, selection of appropriate methodology, estimation of model, and documentation. Developed statistical models, segmentation schemes and data-driven analyses supporting marketing campaigns.

From scratch, developed probability of attrition (PD) models under "competing risks," which results in more accurate prediction.

Performed various data-driven analyses such as unit type churn, area and channel churn, and corporate specific churns, etc.

Prepared large Data including data pull from data mart roll up accounts level data to household level merge and/or set to campaign mail files. Developed macros for repeated data analysis such as response, balance, and channels, etc. NPV calculation using data steps including do loops and arrays.

Bank of America / Fleet Bank, Waltham, MA

03.2001 – 03.2004

Sr. Statistician

Conducted direct marketing campaign analysis such as listing, tracking, analysis of campaign variables (audiences, offers, messages, and channels), and campaign measurement (response /activation, account balance, channel usage, attrition/retention, and profitability.)

Developed and improved campaign measurement and analytical approaches that can effectively be utilized for solving business issues, such as customer age, gender, marital status, branch distance, tenure, and mail exposure etc.

Conducted cost benefit analysis of campaign projects using standard metrics such as NPV and IRR.

Conducted and completed various campaign and pre campaign analyses: Small Business Service (SBS) Lead Generation Analysis, SBS Trade-Up Analysis, various SBS BCE Analyses, Retail ATM Analysis, New DDA Profiling, Debit Card Increased Usage, Debit Card Activation, Debit Card Profiling, and Debit Card Targeting Strategy.

Performed data processing including data pull from data mart in UNIX platform, roll up accounts level data to household level, merge and/or set to campaign mail files. Write macros for repeated data analysis such as response, balance, and channels, etc. NPV calculation using data steps including do loops and arrays.

Worked on setting up campaigns for production of marketing campaign populations. Coordinated inflow and outflow of fields into campaign data. Created and cut mailing list for production.

Provided guidance to other team members. Analysis measures include campaign offers, response/activation, account balance, channel usage, attrition/retention, duration, and campaign profitability (NPV).

ADDITIONAL WORK EXPERIENCE

Wolters Kluwer Financial Services - Boston, MA

01.2006 – 10.2007

Sr. Statistician

Developed statistical models to account for racial denial and pricing disparities in defending a bank’s right against fair lending charges of OTS.

Successfully accounted for disparities using important determinants of underwriting or pricing decisions, such as credit scores, loan-to-value ratio, debt-to-income and others.

Developed predictive models in loan pricing and decision (approval/decline) for disparities analysis in the “Fair Lending Wizard Web” for their bank clients.

Massachusetts Institute of Technology (MIT), Cambridge, MA

10.2003 – 05.2004

Sr. Economist Consultant

Developed the Linear Expenditure Model to estimate demand on telecom services - fixed phone line access, mobile access, Internet access, broadband, and cable/satellite TV.

Estimated income, price and cross price elasticity of telecom services.

Developed econometric model to measure the regulatory impacts on telecom investments in the context of the Telecom Act of 1996 promoting competition by requiring provision of Unbundled Network Elements (UNE's) of the Incumbent Local Exchange Carrier (ILEC).

Clinical Trials / Credit – Bloomingdale, IL

10.1996 – 03.2001

Sr. SAS Programmer

Built various models such as response, Tobit model, probability of default, and hazard models.

Performed data processing including data pull from data mart in UNIX platform.

Utilized UNIX shell scripts to manage SAS jobs.

Developed SAS programs and extensively used SAS macros and put statement for data management, statistical analysis and report generation, such as derived data set, statistical tables, data listings, and graphs to fit statistical plan.

Applied knowledge of statistics to fulfill primary duties, and used SAS/Base, SAS/Macro, SAS/SQL, SAS/Graph, and SAS/Stat Procedures including Proc UNIVARIATE, Proc FREQ, Proc MEANS, Proc CORR, Proc GLM, Proc LOGISTIC, Proc LIFETEST, and Proc PHREG.

Reviewed work for quality, accuracy, and adherence to company’s systems and procedures as to improve productivity, accuracy, quality, and ease of modification

SKILLS

SAS/Base, SAS/Macro, SAS/Stat, SAS/SQL, SAS/JMP, SAS Enterprise Guide, SAS High-Performance Forecasting/SAS Forecast Studio, SAS Enterprise Miner, IKM TeckChek SAS Test Score: 93/100

EDUCATION

Ph.D. Major Courses in Economics/Ag. Economics, and Statistics, OSU, Columbus, Ohio

M.S. Economics, The Ohio State University (OSU), Columbus, Ohio

B.S. Agricultural Economics, University of Hohenheim, Baden-Württemberg, Germany

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