Curriculum Vitae

Sayantani Chatterjee

Educational credentials

Contact Info

Phone +91 9804371125

E-mail Sayantanirahul@gmail.com

Permanent Address IA 236 Salt Lake City Sector 3 Kolkata 700097

Basic Info

Sex Female

Nationality Indian

Marital Status Single

DOB 6/12/1992

From Kolkata,India

Lives in Mumbai,India

Skills

SAS 9.1 BASE ADVANCED

R

VBA

SPSS

C

MICROSOFT OFFICE

Operating System covers Windows Family

About

I am an ambitious and goal-oriented young student

currently pursuing Masters’ degree In Population

Studies. I want to blend creativity to work in a company

which offers challenging and interesting data analysis

with my unique knowledge of Statistics,Population

Studies and Analytics.

My ultimate objective is to develop myself as a skilled

research worker in Mathematical demographic field.

Examination Subjects Institution/Board Year of passing

Percentage of marks

10th

Standard

Bengal(I & II),English,Physical Science,Life Science,History,Geography,Mathematics, Additional Mathematics(optional elective)

Gokhale Memorial Girls’ School, West Bengal Board of Secondary Education

2009

86.3%

12th

Standard

Bengali,English,Physics,Chemistry,Mathematics, Statistics ,Environmental Science

Gokhale Memorial Girls’ School, West Bengal Board of Higher Secondary Education

2011

80.25%

Honours Graduation

B.Sc Statistics (H), Economics, Mathematics Bidhannagar Government College,West Bengal State University

2014 64.63% (H)

Post Graduation

M.Sc Population Studies International Institute for Population Sciences,Deemed University

2014-Present

7.28 in a scale of 9(Sem 1 and 2)

Key Skill Set SAS,Analytics,Data handling

Expertise

Expertise in analyzing and coordinating data, generating

reports, tables, listings and graphs

Optimize performance in Data Analysis

Statistical procedures like PROC FREQ, PROC MEANS, and PROC

UNIVARIATE

Generate reports either in HTML, PDF or RTF formats according

to the client specifications

Analyze the results obtained from various statistical

procedures like PROC ANOVA, GLM and mixed models

Extensive use of PROC SQL to perform queries, join tables, etc.

Conducted analysis and generated tables, listings and graphs

using SAS

Used “data _null_ and PROC REPORT” to generate the outputs

Exploratory data Analysis (EDA)

Descriptive Statistics of the variables using Proc Univariate

Procedure

Problem of Estimation and Testing of Hypothesis, t-Tests , Chi

– square Tests and Analysis of Variance

Correlation and Linear Regression, categorical data analysis

and Logistic Regression

Segmentation techniques: Cluster Analysis

Factor Analysis

Professional

Trainings

SAS BASE

SAS ADVANCED

DATA ANALYTICS and SAS 9.1

R

VBA

SPSS

(Certification is due)

Language proficiency

English

Hindi

Bengali

Projects and Case Studies

Project on Employee Satisfaction Survey at OrangeTree Global

Worked on a project related to HR domain to find out the key factors influencing Employee

Satisfaction and the factors need to be considered to retain the employees using Factor Analysis.

There were some step wise checking for the validity of the models base on some parameters

once the final segmentations solutions are reached.

The above mention step wise check includes Correlation coefficient matrix, KMO MSA Test, Scree

Plot, Eigen values.

Construction of Final factors from final data set by suitable techniques.

Project on Time series Forecasting base on Airline data at OrangeTree Global

Worked on a project on Demand Forecasting for an Airline based on past data sets on number of

passengers.

There was a rigorous check for non – stationarity in the data and the methodology involved the

removal of non – stationarity for the data by taking some suitable mathematical transformation.

It involved methodologies like ARMA and ARIMA to come to a series of forecasted figures of the

future time period using SAS.

We conducted ADF test to check for the stationarity and presence of Unit root in the data.

For the order of ARMA and ARIMA we have considered the ACF and PACF plots.

Project on Time series Forecasting base on Sales data at OrangeTree Global

Worked on a project related to sales of an organization where future sales could be forecasted

using the various techniques of smoothing out the random fluctuations.

The main methodology used for smoothing out the random fluctuations were simple exponential

smoothing and winter‟s exponential smoothing.

We have also used Autoregressive process to do the forecasting for the above mentioned

project.

Project on segmentation in Sports Analytics at OrangeTree Global

Worked on a project which segregates various cricket players based on the performance matrix

provided in the data. There were information given for the batsmen and bowlers. The objective

of the study was to find out the segments having best batsmen and best bowlers from the data.

Cluster Analysis technique was applied to do the segmentation on the data and this included

both agglomerative and divisive hierarchical clustering to get the initial idea about the number

of clusters in the data.

After getting the number of clusters, K – means clustering techniques was used to identify the

players in the clusters.

Finally there was a univariate Analysis done to profile the cluster and then interpretation the

clusters to reach at a final solution.

Project on Credit Risk Modeling at OrangeTree Global

Worked on a project related to Financial Markets wherein I had to examine the trust worthiness

of a prospective customer and his/her possibility of defaulting on loan.

The task was to build a Behavioural Credit Risk Model based on a large sample of data by

applying Logistic Regression on the SAS platform.

The data had various information related to behaviour transactional details of the customers

and their performance in repayment.

There were number of validation checks which were performed to test the robustness of the

model under taken in terms of various goodness – of – fit statistics.

There were number of goodness of fit statistics which we had considered like Percent

Concordant, Hosmer – Lemeshow test, Wald – chi square and score tests.

Project on Customer Satisfaction Survey at OrangeTree Global

Worked on a project related to retail domain based on Customer Satisfaction Survey where the

objective was to find out the key factors influencing the overall customer satisfaction using OLS

Regression.

There were some rigorous checks in terms of data hygiene check, basic exploratory analysis on

the data was performed to get better understanding of the data and the model that can be used

on the data to solve the business problem.

There were number of validation checks which were preformed to test the robustness of the

model under taken in terms of various goodness – of – fit statistics.

We looked into Adjusted R square, F statistics, and VIF values for goodness of the model and for

selecting the optimum number of variable to be considered.

The result got from the training set was then applied on the validation or hold out set to check

the robustness of the model.

Project on Testing of Hypothesis on Clinical data at OrangeTree Global

Worked on a case study about Blood Pressure of different respondent pertaining to Clinical

Research to check whether the average blood pressure in the population was equal to

hypothesised value or not.

This was done by first checking the normality of the variable under consideration and then

doing of one sample t – test on it.

We have constructed the confidence intervals and then check whether true population mean

value falls in the derived interval or not.

Project on Testing of Hypothesis on Automobile data at OrangeTree Global

Worked on a case study related to Automobile Industry for finding out which Automobile

company is more efficient in product delivery.

We have applied Analysis of variance(ANOVA) technique to do the analysis and the data was

collected from three leading Automobile company on the delivery speed.

We have performed a thorough F – test on the data to find out which one is more efficient in

their delivery speed.

Project on Analysis of Two-Way ANOVA on Clinical Trial Data related to weight gain of

individuals at OrangeTree Global

The project involved a Two – way analysis also which talk about an interaction between the two

factors i.e. diet amount and diet type. We tried to find out whether there exists any type of

interaction effect in the data on weight gain of individuals or not.

We have applied the Tukey‟s mean test to find out which categorical variable, out of „diet type‟

and „diet amount‟ has a significant impact on the weight gain of individuals.

Project on Time series Forecasting base on Sales data at OrangeTree Global Worked on a project related to sales of an organization where future sales could be forecasted using the

various techniques of smoothing out the random fluctuations.

The main methodology used for smoothing out the random fluctuations were simple exponential smoothing

and winter’s exponential smoothing.

We have also used Autoregressive process to do the forecasting for the above mentioned project.

Strengths

Self-confidence and positive approach

Fast learner & hard worker

Innovative thinking

Highly motivated individual with excellent organizational and

interpersonal skills

Possess strong ability to quickly adapt to new applications and

platforms.

Ability to write some common macros that are useful across

multiple studies.

Extra Curricular Activities & Hobbies

Reading:Bengali Classic Literature

is my favourite genre

Cooking:delicious items

Achievements

Central Government stipend holder

First class First in B.Sc(H)

Served as School Captain(2007-

2008)

I hereby declare that the information furnished above is true to the best of my knowledge.

PLACE: Kolkata -------------------------------

DATE: 1/6/2015 (Sayantani Chatterjee)

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