Project Data
Resume:
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SRIKANTH KUMAR NELANTI
email: ****************@*****.**.**
Phone: 302-***-****
Stillwater, OK 74075
Objective
Highly dedicated graduate student with strong analytical, communication and
innovative skills with 4 years of experience seeks full-time opportunity in
the field of Business Analytics and Data Mining.
Education
MS in Management Information Systems Grad: Jul 2010
GPA: 3.86/4.0
Oklahoma State University, Stillwater, OK
Master of Management Studies Grad: May 2005
GPA: 3.8/4.0
Birla Institute of Technology and Science, Pilani, India
Total Experience: 4 years
Functional Skills
In depth knowledge of Database marketing, data mining using predictive
modeling techniques, data preprocessing and data analysis.
Profound knowledge of forecasting techniques like regression, decision
trees, neural networks, multivariate analysis, CRM, time series analysis,
cluster and factor analysis, conjoint analysis, SEM.
Expertise in Base SAS programming including advanced techniques like Proc
SQL and Macros processing.
Domain knowledge of financial markets and instruments and health care.
Technical Skills
Databases : Oracle 8i/9i, MS Access, MS SQL
Analysis software : SAS Enterprise Guide, SAS Enterprise Miner, SAS
9, SPSS Clementine, Stata, Gretl, R
Languages : C, Java, VB 6.0, SQL, PL/SQL, VB.NET, PHP, ABAP/4
Enterprise software : SAP R/3
Other tools : Microstrategy, Rational Rose, Mercury QC, Visio,
Project, MS Word and Excel
Technologies : XML, ASP.NET, ADO.NET, JavaScript, HTML, CSS
Operating Systems : Windows 9x/NT/2000/XP/Vista, UNIX
Professional Experience
Business Analyst Jul
2006 to Jul 2008
ANZ Operations and Technology Pvt. Ltd., India
Client: ANZ Banking Group, Australia
. Research on web analytics, determining search engine components and
providing recommendations.
. Detailed study of the online marketing strategy of ANZ through web
tracking, analysing and reporting the web analytic reports.
. Tracking the online and email campaigns of various business units and
providing analysis reports on the progress.
. Building statistical predictive models for designing targeted online
and email campaigns using various data mining techniques.
. Requirements gathering, project scoping and detailed documentation for
all the Online Applications, new web-based eCommerce applications of
ANZ and affiliates.
. Ownership of the change management process, ensure successful
implementations through pre-UAT, software verification and validation
and post implementation validations.
. Responsible for establishing and streamlining processes to improve the
operational efficiency.
Business Analyst
Jun 2005 to Jul 2006
HCL Technologies Ltd., India
Client: Countrywide Financial Corporation, U.S.A.
. Worked on requirements gathering, documentation of Due Diligence
Automation system along with stakeholder interactions and facilitating
UAT.
. Worked on business process study, requirements analysis and
documentation of the Business Engagement Management System, a sales
force automation tool for HCL Technologies Ltd. Involved in writing
project artifacts including database design documents.
Software Developer
Jul 2004 to Dec 2004
Intelligroup Asia Pvt. Ltd., India
Client: Bristol-Myers Squibb, U.S.A.
Worked on various tasks as Developer and Tester across multiple functional
modules. Collaborated with the client BMS in USA to successfully execute
several SAP modules. Involved in application development, peer reviews of
code and test cases, unit testing and defect fixing.
Data Mining Projects
Client: Oklahoma State Department of Health
Project: Predicting factors that contribute to the denial of Medicaid
Insurance to customers
Task: A 4-month long real-time project that dealt with building robust
models to predict the likely factors which contribute to the denial of
Medicaid Insurance for customers.
Role:
. Understanding of the data
. Client interactions for detailed business process study
. Cleansing of the data using Base SAS, SAS Enterprise Guide and
Enterprise Miner
. Preliminary analysis of data using techniques like crosstabs and ANOVA
. Building various models like decision trees, regressions, neural
networks
. Evaluation of the models using fit statistics and domain knowledge
. Model optimization
. Reporting the factors to the client along with optimizing the results
Competition: SAS Data Mining Shootout M2009
Project: Prediction of Energy grass yield based on soil and weather
conditions
Task: Built a ranking model to rank the top three states and counties in
the US with respect to the energy grass densities based on the soil and
weather conditions.
Role:
. Data understanding and cleaning
. Model building using various techniques
. Model evaluation using various goodness of fit statistics
. Ranking the data
. Documenting and Reporting the results and observations to the M2009
committee
Course: Business Intelligence Tools and Techniques
Project: Classification of Customers for Check -out coupons
Task: Project involves identifying whether a customer is a potential
customer and depending on his potential to return to the store, the type of
coupon to be issued to him as a part of sales promotional activity is
predicted.
Role:
. Understanding the data and cleaning data for missing values
. Model building and model evaluation
. Recommend a robust data mining model to predict the type of coupons to
be issued in the later years.
Course: Database Marketing
Project: Model Selection for scoring the house-file of a catalogue company
Task: The main objective is to build a good regression model that predicts
the 'amount of orders' on calibration data and use that model to score the
rest of the house file of the catalog company.
Role:
. Data understanding
. Preliminary analysis
. Model building using linear and logistic regression
. Model evaluation
Course: Database Marketing
Project: Predicting people's Response for buying in a mail campaign
Task: Building a predictive model to predict the potential customers who
are most likely to buy and include them in the mailing campaign for this
year. The model built should improve the profits being generated.
Role:
. Data pre-processing
. Model building using RFM and logistic regression techniques
. Reporting the findings based on the decile analysis of the predictions
from data mining techniques
Academic Experience
. Currently working with Dr. Marilyn Kletke as a Teaching Assistant in
the department of Management Science and Information Systems.
Certifications and Trainings
. Certified Advanced SAS 9 Programmer
. Certified Base SAS 9 Programmer
. Awarded with SAS/OSU Certification in Data Mining
. Certified in SAS Predictive Modeling
. Completed specialized trainings on 'Requirements Management' and 'Use
Case Modeling' at Melbourne, Australia
Contact this candidate