Data Project

Geeta Dalvi **** W Woods Dr. Apt ***, Arlington Heights, IL, 60004

E-mail: ************@*****.***

Mobile: 405-***-****

Summary

. Predictive Modeler & BASE SAS Certified with Statistical Analysis &

Modeling using SAS, SPSS & Tableau

. Experience in segmentation, Decision Tree, prediction, hypothesis

testing, regression and report building

. Advanced knowledge of SQL, Data Analysis in Excel, Google Analytics,

presentations & Microsoft Project

. PHR Certified and work experience in Organization Development, Training

& Performance Management System, employee Development, Talent Management

and employee engagement

Education Certifications

Master of Management Information Systems SAS Certified Base

May 2013 Programmer Dec

(GPA 3.8/4.0) 13, 2012

Oklahoma State University

(Specialization: Data Mining, Knowledge Management) SAS Predictive Modeler

April, 2013

Graduate Certificate

in Data Mining

April, 2013

Professional in Human

Resources (PHR)

Dec 2010

Master of Labor Studies June 2005

University of Mumbai, India

(Specialization in Manpower Planning, Training &

Development,

Organization Behavior & Organization Development)

Bachelor of Computer Science May 2003

University of Mumbai, India

Technical Skills

. Statistical and Analytical Tools: BASE SAS 9.0, SAS Enterprise Guide, IBM

SPSS, Tableau, Google Analytics

. Project Management and Collaboration tools: MS Project, Visio

. Database Management Systems: SQL Server, Microsoft Access

Experience

Senior Analyst, Cogensia, a CAC Group Company, IL

November 2013 - Present

. Formulate data into a variety of analysis and presentation formats that

best match the client's needs

. Data Exploration and Analysis on raw data from client

. Programming in SAS for creating Datasets, Data manipulation, Reports,

Tables, Listings & Graphs

. Developing and automating detailed reports using both SAS and Excel; and

making recommendations

. Conduct analysis answering specific client questions about brands,

products, competitors, or campaigns

. Running production processes on monthly or weekly cadence

. Build response model for a clients new marketing campaign

Summer Intern, Data Analysis and Reporting, ISNetworld Dallas, TX

June 3 - August 9, 2013

. Handled customer segmentation and business analysis request,

presented results to management

. Used Regression & Decision tree in SAS Enterprise Guide for

predictive analysis of customer attrition

. Assisted team members with day-to-day activities of preparing,

mining, analyzing & reporting data

. Participated in the development of business indicators and

benchmarking reports to be used by clients

. Presented analysis results, methods and findings to stakeholders,

verbally and in written format

OSU and SAS Data Mining Program

Jan 2012 - Jun 2013

. Worked on hypothesis testing, statistical test like Two Sample t-

Test, Paired sample test, ANNOVA

. Performed Regression, Decision Tree, Neural Network and Logistic

regression modeling

. Handled data from different formats and used BASE SAS to import,

merge, transform and clean data

. Used correlation, P value, Chi Square for statistical analysis

. Worked on survey design, report building & used database marketing

concepts for survey analysis

Manager Human Resources, Mahindra & Mahindra Ltd. Mumbai, India

Feb 2008-Jan 2010

. Carried out Employee Engagement activities that helped organization

control attrition rate

. Conducted Gallup Survey and designed interventions to address survey

outcomes

. Performed annual employee Assessment that also involved ensuring

appraisal authenticity and guidelines

. Created employee connect through induction process,Mentor & Buddy System

. Designed Competency Modeling and Mapping for a set of employees for

effective assessment

Projects

Prediction of Customer Attrition

This project focused on identifying customer with high risk of not

renewing their contract. I used 3 years of company proprietary data for

this project. Preformed summary statistics cross tab analysis, ANOVA,

variable selection and logistic regression, neural network, decision tree

to predict customer churn.

Crime Data Analysis

Aim of this project was to identify factors other than poverty and

unemployment that affect crime rate. Socio-economic and law enforcement

data from census and survey was used. Tableau and SAS models were used to

understand relationships, distributions, visualize trends, explore and

describe data and predict crime rate.

Predicting Customer Response for Insurance re-quote offer

It involved analyzing customer data for to a leading insurance company in

USA to predict customers with positive response for company's re-quote

offer. Key variables contributing to the customer response were

identified using regression, neural network and decision tree.

Advanced System Analysis and Design

Learned different approaches of SDLC and gained knowledge about Agile

methodology

Studied key concepts of software application focused problem

understanding, requirement gathering with use cases, UML diagrams, DFD, E-

R diagram and Logical & Physical database design.

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