sample resume_sas analytics

8/13/2019 Sample Resume_SAS Analytics

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Rajiv MukherjeePersonal Information

Sex Female

Nationality INDIAN

Marital Status Single

Date Of Birth April 20th 1986

Permanent Address &Phone #

86-A / H / 6 / 1-B Christopher oa!"#ol$ata% &in Co!e ' (00 0)6%*est Bengal" In!ia&hone + , 0091 - - 229 (10

Key Skill Set SAS Anal.tis BA

Expertise

hoose any ! Areas "e sure that you kno e$erythin%there is to kno a"out the points you ha$e hosen''

pertise in anal.3ing an! oor!inating !ata" generating reports"ta4les" listings an! graphs

5ptimi3e perormane in Data Anal.sis

Statistial proe!7res li$e &5C F" &5C ANS" an! &5C:NIAIA;

e Statistis o the >aria4les 7sing &ro :ni>ariate&roe!7re

&ro4lem o stimation an! ;esting o H.pothesis" t-;ests " Chi 's?7are ;ests an! Anal.sis o ariane

Correlation an! =inear egression" ategorial !ata anal.sis an!=ogisti egression

Segmentation tehni?7es, Cl7ster Anal.sis

Fator Anal.sis

;ime Series Anal.sis 47il!ing AIA mo!el" AIA mo!el

Base C=

A!>ane el BA maro

Work Experience (Please omit if you are a fresher')

Name Of *he Or%ani+ation HCFS Ban$

Desi%nation Senior anager

Proess Name Clo>er


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*enure No>em4er 2010- ;ill Date

Name Of *he Or%ani+ation HSBC

Desi%nation Asst anager

Proess Name Clo>er

*enure No>em4er 2009' No>em4er 2010

Name Of *he Or%ani+ation HDFC Ban$

Desi%nation anagement ;rainee

Proess Name Clo>er

*enure G7l. 2009 ' No>em4er 2009

Academic Qualifications

Eduation Post-Graduation Graduationi!her"econdar#Class 12E

"econdar#Class 10E

De%ree , Streamaster o Siene%S% onomisE

Bahelor oSiene

B%S%onomisHono7rsE

Higher Seon!ar.Seon!ar.amination

-ear 2009 200( 200) 2002

Perenta%e 66% 66 (8 80

Main Su".ets onomisonomis"athematis"Statistis

athematis"Statistis"onomis" o-ersit.

Cal7tta:ni>ersit.College,Basanti De>iCollege"#ol$ataE

*est Bengal Boar!Shooling, &athaBha>an" #ol$ata E

*est BengalBoar!Shooling, Hol.Chil!" #ol$ata E

Professional $rainin! % &ertification&ertifications SAS Anal.tis BA Certiiation rom

'ran!e$ree Glo(al

Professional $rainin!s SAS BAS

SAS ADANCD


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0reat' So far so %ood' No the folloin% area is ruial1 2emem"er that most youould not ha$e any experiene in SAS Analytis3 the folloin% se%ment on4Pro.ets5 is there to fous on the fat that you ha$e "een in$ol$ed in anum"er of ase Studies,Simulated Pro.ets durin% your pro%ram here12emem"er to hoose 6 to ! Pro.ets "ut hoose isely1 Selet ases studieshih ha$e a rele$ane to the .o" you ha$e applied for herein you an 7shooff5 you knoled%e in Analytis ith ease and onfidene'

Projects and &ase "tudies

Project on &redit Risk Modelin! at 'ran!e$ree Glo(al

*or$e! on a pro@et relate! to Finanial ar$ets Jherein I ha! to eamine the tr7st

Jorthiness o a prospeti>e 7stomer an! his/her possi4ilit. o !ea7lting on loan%

;he tas$ Jas to 47il! a Behavioural Credit Risk Model4ase! on a large sample o !ata 4.

appl.ing =ogisti egression on the SAS platorm%

;he !ata ha! >ario7s inormation relate! to 4eha>io7r transational !etails o the7stomers an! their perormane in repa.ment%

;here Jere n7m4er o >ali!ation he$s Jhih Jere perorme! to test the ro47stness o

the mo!el 7n!er ta$en in terms o >ario7s goo!ness ' o ' it statistis%

;here Jere n7m4er o goo!ness o it statistis Jhih Je ha! onsi!ere! li$e &erent

Conor!ant" Hosmer ' =emeshoJ test" *al! ' hi s?7are an! sore tests%

Project on &ustomer "atisfaction "urve# at 'ran!e$ree Glo(al

*or$e! on a pro@et relate! to retail !omain 4ase! on Customer Satisfaction SurveyJherethe o4@eti>e Jas to in! o7t the $e. ators inl7ening the o>erall 7stomer satisation7sing 5=S egression%

;here Jere some rigoro7s he$s in terms o !ata h.giene he$" 4asi eplorator.anal.sis on the !ata Jas perorme! to get 4etter 7n!erstan!ing o the !ata an! the mo!elthat an 4e 7se! on the !ata to sol>e the 47siness pro4lem%

;here Jere n7m4er o >ali!ation he$s Jhih Jere preorme! to test the ro47stness othe mo!el 7n!er ta$en in terms o >ario7s goo!ness ' o ' it statistis%

*e loo$e! into A!@7ste! s?7are" F statistis" an! IF >al7es or goo!ness o the mo!elan! or seleting the optim7m n7m4er o >aria4le to 4e onsi!ere!%

;he res7lt got rom the training set Jas then applie! on the >ali!ation or hol! o7t set tohe$ the ro47stness o the mo!el%

Project on Emplo#ee "atisfaction "urve# at 'ran!e$ree Glo(al

*or$e! on a pro@et relate! to H !omain to in! o7t the $e. ators inl7ening Employee

Satisfactionan! the ators nee! to 4e onsi!ere! to retain the emplo.ees 7sing Fator

Anal.sis%

;here Jere some step Jise he$ing or the >ali!it. o the mo!els 4ase on some

parameters one the inal segmentations sol7tions are reahe!%

;he a4o>e mention step Jise he$ inl7!es Correlation oeiient matri" #5 SA ;est"

Sree &lot" igen >al7es%

Constr7tion o Final ators rom inal !ata set 4. s7ita4le tehni?7es%


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Project on $ime series )orecastin! (ase on Airline data at 'ran!e$ree

Glo(al

*or$e! on a pro@et on Demand Forecastingor an Airline 4ase! on past !ata sets on

n7m4er o passengers%

;here Jas a rigoro7s he$ or non ' stationarit. in the !ata an! the metho!olog. in>ol>e!

the remo>al o non ' stationarit. or the !ata 4. ta$ing some s7ita4le mathematial

transormation%

It in>ol>e! metho!ologies li$e AA an! AIA to ome to a series o oreaste! ig7res o

the 7t7re time perio! 7sing SAS%

*e on!7te! ADF test to he$ or the stationarit. an! presene o :nit root in the !ata%

For the or!er o AA an! AIA Je ha>e onsi!ere! the ACF an! &ACF plots%

Project on $ime series )orecastin! (ase on "ales data at 'ran!e$ree

Glo(al

*or$e! on a pro@et relate! to sales o an organi3ation Jhere 7t7re sales o7l! 4e

oreaste! 7sing the >ario7s tehni?7es o smoothing o7t the ran!om l7t7ations%

;he main metho!olog. 7se! or smoothing o7t the ran!om l7t7ations Jere simple

eponential smoothing an! JinterKs eponential smoothing%

*e ha>e also 7se! A7toregressi>e proess to !o the oreasting or the a4o>e mentione!

pro@et%

Project on se!mentation in "ports Anal#tics at 'ran!e$ree Glo(al

*or$e! on a pro@et Jhih segregates >ario7s ri$et pla.ers 4ase! on the perormane

matri pro>i!e! in the !ata% ;here Jere inormation gi>en or the 4atsmen an! 4oJlers%

;he o4@eti>e o the st7!. Jas to in! o7t the segments ha>ing 4est 4atsmen an! 4est

4oJlers rom the !ata%

Cl7ster Anal.sis tehni?7e Jas applie! to !o the segmentation on the !ata an! this

inl7!e! 4oth agglomerati>e an! !i>isi>e hierarhial l7stering to get the initial i!ea

a4o7t the n7m4er o l7sters in the !ata%

Ater getting the n7m4er o l7sters" # ' means l7stering tehni?7es Jas 7se! to i!enti.

the pla.ers in the l7sters%

Finall. there Jas a 7ni>ariate Anal.sis !one to proile the l7ster an! then interpretation

the l7sters to reah at a inal sol7tion%

Project on $estin! of #pothesis on &linical data at 'ran!e$ree Glo(al

*or$e! on a ase st7!. a4o7t Bloo! &ress7re o !ierent respon!ent pertaining to Clinical

Research to he$ Jhether the a>erage 4loo! press7re in the pop7lation Jas e?7al toh.pothesise! >al7e or not%


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;his Jas !one 4. irst he$ing the normalit. o the >aria4le 7n!er onsi!eration an! then

!oing o one sample t ' test on it%

*e ha>e onstr7te! the oni!ene inter>als an! then he$ Jhether tr7e pop7lation

mean >al7e alls in the !eri>e! inter>al or not%

Project on $estin! of #pothesis on Automo(ile data at 'ran!e$ree

Glo(al

*or$e! on a ase st7!. relate! toAutomobile ndustry or in!ing o7t Jhih A7tomo4ile

ompan. is more eiient in pro!7t !eli>er.%

*e ha>e applie! Anal.sis o >arianeAN5AE tehni?7e to !o the anal.sis an! the !ata

Jas ollete! rom three lea!ing A7tomo4ile ompan. on the !eli>er. spee!%

*e ha>e perorme! a thoro7gh F ' test on the !ata to in! o7t Jhih one is more eiient

in their !eli>er. spee!%

Project on Anal#sis of $*o-Wa# A+',A on &linical $rial ata related to

*ei!ht !ain of individuals at 'ran!e$ree Glo(al

;he pro@et in>ol>e! a ;Jo ' Ja. anal.sis also Jhih tal$ a4o7t an interation 4etJeen the

tJo ators i%e% !iet amo7nt an! !iet t.pe% *e trie! to in! o7t Jhether there eists an.

t.pe o interation eet in the !ata on Jeight gain o in!i>i!7als or not%

*e ha>e applie! the ;7$e.Ks mean test to in! o7t Jhih ategorial >aria4le" o7t o L!iet

t.peK an! L!iet amo7ntK has a signiiant impat on the Jeight gain o in!i>i!7als%

"tren!ths

Stren%ths

hoose 8 to 6 Areas "ut remem"er that the inter$ieer ill%enerally ask you to ite an example here you displayed that

partiular stren%th1 So ha$e examples ready1

Sel-oni!ene an! positi>e approah

Fast learner M har! Jor$er

Inno>ati>e thin$ing Highl. moti>ate! in!i>i!7al Jith eellent organi3ational an!

interpersonal s$ills

&ossess strong a4ilit. to ?7i$l. a!apt to neJ appliations an!platorms%

A4ilit. to Jrite some ommon maros that are 7se7l aross m7ltiplest7!ies%

A4ilit. to Jor$ on m7ltiple pro@ets sim7ltaneo7sl. an! meet !ea!lines

Proficienc# in .an!ua!es

nglish" Bengali M Hin!i

Extra &urricular Activities / o((ies


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Be sli%htly detailed1 *his area ill %i$e the inter$ieer additional insi%hts into yourpersonality and harater1 A$oid mundane sentenes like 49 like readin%3sin%in%3 danin%3 paintin%3 playin% riket :et5 9f you like readin% %i$e a listof your fa$orite authors and some of your fa$orite "ooks1 Danin%;

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