Software Engineer Marketing

PRAMODA. B. SRINIVASAMURTHY

***** ******** ****, *** ***, North Hollywood, CA - 91601

Contact: 405-***-**** ? E-mail: ablyxm@r.postjobfree.com, ablyxm@r.postjobfree.com

OBJECTIVE:

Seeking a responsible and challenging position as a Predictive Modeler/Data

Analyst/SAS Programmer/Business Analyst/Marketing Analyst. To be a part of

an organization that is progressive, in which I can utilize my current

skills and knowledge as well as expand them to assist the success of the

organization.

EDUCATION:

. William S. Spears School of Business

Aug'08 -May'10

Oklahoma State University, Stillwater

Masters in Management Information Systems (GPA: 3.7/4.0) (GRE:

1300/1600 TOFEL: 108/120)

SAS Certified Base Programmer for SAS 9.

SAS Certified Advance Base SAS Programmer for SAS 9.

SAS Certified Predictive Modeler using SAS Enterprise Miner 5.3.

SAS/OSU - Data Mining Certified.

. Visvesvaraya Technological University, India

Sep'01 - Jun'05

Bachelor of Engineering, Telecommunications

PROFESSIONAL EXPERIENCE:

Graduate Research Assistant

Aug' 08

-May'10

Department of Management Science &Information Systems, OSU

. Working with Dr. Goutam Chakraborty, Professor, Department of

Marketing, in identifying most valuable customers for loyalty program

of a Travel Stop.

. Working with Dr. Goutam Chakraborty, Professor, Department of

Marketing, in Survey Data Analysis for a Travel Stop. The project

involves Cluster Analysis, Text mining and Predictive modeling using

SAS Enterprise Guide, SAS Enterprise Miner and Base SAS Programming.

. Working with Dr. Goutam Chakraborty, Professor, Department of

Marketing, for a B2B company in the Construction Industry. The project

deals with models building using SAS Enterprise Guide, SAS Enterprise

Miner and Base SAS Programming.

. Grading and Proctoring for Data Base Marketing and also Data Mining

&CRM Applications courses where students use SAS Enterprise Guide, SAS

Miner & Base SAS (as a part of the teaching assistant ship by the

department.). Responsible for clarification of any kind of SAS related

queries and doubts by the students both in their exercises and real

time projects.

Graduate Research Assistant (Network Administrator)

Aug' 08 -

Dec'09

Institute of Research in Information Systems (IRIS), Department of

Management Science & Information Systems, OSU

. Secured websites against threats and malware.

. Involves maintaining databases for Defense Ammunition Center.

. Trouble shooting hardware &software problems (includes Windows

optiplex systems, Windows 2003 servers, HP printers, Dell

printers.) &regularly backup websites, systems &databases.

Senior Software Engineer (Testing Services)

Sep' 05 - May'08

Alcatel-Lucent's Access Management System at Wipro Technologies, India

. Developed comprehensive test case documents, executed test cases,raised bugs with a very low rejection ratio (5% rejection of the

total bugs)

. Involved in all stages of STLC (Software testing life cycle).

. Successfully allocated work & managed daily status report of the team.

. Configured end to end traffic in the lab using elements such as GPON

&G6 in the lab.

. Trained new associates pertaining to Element Management Layer of the

Telecommunication networks.

TECHNICAL PROFICIENCY:

Enterprise Software: SAS Enterprise

Guide, SAS Enterprise Miner, Base SAS, SPSS, SAP ECC

Packages Known: MS Office

97/2000/XP/2003/2007, MS Project, PowerPoint,

Visio, Prosim, AI0Win7.0

Operating Systems: Macintosh, Solaris, Windows NT/9X, 2000, XP, VISTA,

UNIX, Linux, DOS.

Development/Productivity Tools: SQL, Perl, HTML, JavaScript, XML, C,

TCL/TK, Shell Scripting

PROJECTS UNDERTAKEN:

Predictive Modeling for OSDH (Oklahoma State Health Department)

Built a Predictive model for a client to analyze & decrease the number

of Medicaid denials because of non renewals, which helped them to

recoup the lost dollars by developing a targeted campaign. Used SAS

EM, SAS EG and BASE SAS. Modeling was done using Neural Network,

Decision Trees, Regression, and Ensemble models.

Predictive Modeling for M2009 SAS Data Mining Shootout.

The model predicted yields and acreages for a crop and listed the

places where the yields would be maximized. A ranking model with top 3

states and top 3 counties for whole of US for yield of energy grass

was obtained based on various soil and weather conditions. Enterprise

Miner, Enterprise Guide and Base SAS were used in Model building.

Predictive Modeling for M2010 SAS Data Mining Shootout.

The Modeling was done in two stages. In the first stage, BMI is taken

a measure for people who would enroll into the preventive programs; a

prediction model is built to predict people who would contract

diabetes. At the second stage, we try to quantify change that is

caused by the preventive programs; we try to predict the Total Health

Care Expense by taking into account all the factors given.

Predictive Modeling for 3G customer base

Built a Predictive model to predict which customers are likely to

switch from their network to the newly launched (3G) network. The data

had more than 200 variables which were reduced to a few important

variables using domain expertise and techniques like Variable

Reduction. Data mining techniques like Decision Trees, Neural

networks, Regression were used to predict the type of network.

Multiple Regression Model to score the house file of a catalogue

company

Built multiple regression models to predict the total amount of orders

placed by each customer and thus help the Catalogue Company to conduct

effective direct marketing campaign. Various MR models were built

using forward, backward and stepwise variable selection methods,

variable transformation and using various probability cut-off values.

Model with lowest values of Coefficient of variation, MAPE and MSE was

chosen as the best scoring model

Direct Marketing: Predicting response for buying in a mail campaign

using RFM Analysis and Logistic Regression

Performed RFM analysis using both dependent and independent sorting

techniques to create RFM codes and calculated the profit made by

targeting selected customers. Built predictive models using Logistic

regression. Goodness of fit, R-square value and other model fit

statistics were compared across the models to select the best scoring

model.

Sample t-tests: Anti-absenteeism program.

Evaluated the cost effectiveness of the new anti-absenteeism program

implemented at X Inc, using hypothesis testing with paired sample t-

test and two sample t-test. Cost calculations were made and compared

before and after test implementation of the program and the program

was recommended to be continued

Summary Statistics :Employee Bonus Program

Evaluated the fairness of the bonus program at Glenco Manufacturing

Company, using summary statistics. Recommended corrected list of

employees who actually deserve the bonus, by standardizing the

supervisor ratings across departments and analyzing any other possible

reasons for a biased rating based on factors like age, race, sex etc.

Developed of an E-Commerce website

Built Ecommerce site for a Mobile Store, using two different methods.

First, where a dynamic users interface was created by using HTML,

JavaScript, CSS, XML and XSL. In the second phase, the application was

developed using ASP.net with SQL server 2005 as backend

CERTIFICATIONS/AWARDS:

. Winner of SAS Student Scholarship to attend the SAS Global Forum

2010 in Seattle (one in 20 Students selected by SAS from all over

the US.)

. Winner of Student Scholarship to attend M2009 SAS Data Mining

Conference in Las Vegas.

. Winner of Annual Spears School IT Executive Interaction Case

Competition conducted by Spears School of Business.

. Winner of Student Scholarship to attend ITERA annual conference

held in Atlanta, Georgia.

. Winner of three "Feather in my cap" awards from the General

Manager, Wipro Technologies.

. Winner of two "Thanks a Zillion" awards from the Group Head, Wipro

Technologies.

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