SAYONI BISWAS M: 8337031554/8001278925

E-mail:sayoni1biswas.asm@gmail.com

Summary

Become professional analyst or active member of analyst team at any vertical of analytics where my skill set will help middle management to solve the business problem and decision making and serve the client with a robust solution.

System Knowledge

SAS9.2 VBA MINITAB C SPSS20 Microsoft Excel Oracle10g C++ R analytics SQL Core Java

Skills SAS programming linear regression modeling Credit-risk modeling predictive modeling Strategic skills logistic regression modeling Problem solving skills cluster analysis Statistical modeling factor analysis Trend analysis CHAID modeling

Expertise Expertise in analyzing and coordinating data, generating reports, tables, listings and

graphs In depth knowledge in SQL query language Optimize performance in Data Analysis, data clean technique, data analyst Statistical procedures like GLM and marketing mix models, price choice modeling Conducted analysis and generated tables, listings and graphs using SASEnvironment:

SAS/Base, SAS/Stat, SAS/Graph, SAS/SQL, SAS/Macros, SAS/ IML MS-Excel, MIS report generation with charts and graphs Business analysis with predictive modeling and forecasting Segmentation techniques: Cluster Analysis, consumer and retail analytics. Core concepts of marketing strategy and planning In depth knowledge of marketing research methodology Market basket analysis, sentiment analysis, decision tree with R analytics

Industry Experience

1. Duration-2010(decmber)-2011(november) Organization-CMC LTD( TCS) Designation-Software developer Client Name-UIIC

Job Role- A Insurance domain project programming with java struts framework with sql database,job processing to update the transaction and meeting deadlines to release new version

2.Duration-2014 (june)-2014(august) Organization-NIIT LTD Job Role-Member of sales & marketing team, responsible for client servicing, and helping senior manager to take marketing strategy in Below the line(BTL) activity planning and implementation.

3.Duration-2014(October)to till 2015(april)Organization-Orange Tree Global(loc-kolkata)Objective:- Self knowledge development and learning Course details:- 6months regular classroom training program on analytics and statistical modeling based on SAS,R analytics,SPSS,Excel VBA.Area of Interest:- consumer analytics, product-retail analytics, marketing analytics, pricing etc.

Summer Internship Project(PGDM):Name of the Organization : DISH TVDuration : 1/april/2013- 30/MAY/2013\Tool Used : SPSSType : Marketing research AnalysisProject Title : Study and analyse consumer buying behavior in

Fast changing DTH environmentObjective : find target customer in HD segment

PROJECT SYNOPSYS Responsibility: study market trends competitive analysis survey through questionnaire to collect real time data ,study and analyze collected primary

and secondary data through statistical analysis using SPSS tool to solve the business problem and day to day report generation (MIS).

Academic Qualification

Qualification Name of School/College

Board/ University Year of Passing % Scored

PGDM(Marketing & Information technology)

Apeejay School of Management,Delhi

Dimmed university 2012-2014 2.59(4)

B.Tech.(Computer Sc. & Engg)

CEMK WBUT 2006-2010 7.65(10)

XIIth Ramlal Academy WBCHSE 2003-2005 68.4%

Xth B.K.B.V WBBSE 2003 81.0%

CertificationA. Oracle global certification on Oracle certified Java Programmer 6(OCP6)B. Professional course on analytics from Orange tree global(OTG)

Project & case studies on analytics as a trainee (student)at OTG

LIVE project on consumer analyticsProject type: freelancing(bidding )Client type: US firm of north America(agriculture)Deadline:1month Team size:10 Role:Trainee(student)Project details:Client provided a set of questionnaire and sample dataset .They wanted to focus on genetically modified fruit .want a details report on the market scenario on the preference of genetically modified food.Objective: To find consumer group liking genetically modified foodUsed tool:SAS 9.2 ,excel-2010

Case study on Credit Risk Modeling at OrangeTree Global

Worked on a project related to Financial Markets where 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 Behavioral 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 behavior 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 GlobalWorked on a project related to retail domain based on Customer Satisfaction Survey to quantify the major factors from the sample variable and 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 Time series Forecasting base on Sales data at OrangeTree GlobalWorked on a project related to sales of an organization to forecast sales for next five years. main methodology used for smoothing out the random fluctuations was simple exponential smoothing and winter’s exponential smoothing.We have also used Autoregressive process to do

the forecasting for the above mentioned project. There was a rigorous check for non – stationarity ,box jenkins methodology, 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.

HOBBIESNet surfing , listening to music, exploring new things, chess,meditation

PERSONAL PROFILE:DOB: 8/8/1987Marital status: UnmarriedPermanent address: dumdum, sath gachi(natunpalli) ,kolkata-28

PREFERRED LOCATION

Bangalore, Hyderabad, Delhi, Pune, Kolkata, Mumbai