1. RIMPA KUNDU
kundu.rimpa2010@gmail.com 9874425406 DOB: 30th October, 1987
EDUCATION
2017 PGP Business Analytics Praxis Business School, Kolkata.
2010 B-Tech (ECE) RCC Institute of Information Technology 7.97/10
2006 Class XII St Paul’s Mission School 73.8%
2004 Class X St Paul’s Mission School 83.4%
SKILL SETS: SAS, WPS, SQL, Excel, R
PROJECTS
Praxis Business
School
Market Research problem for loan data, customer profiling and customer psychographic Analysis:
Problem: To study a research conducted by a private sector bank to understand town population who have taken
loans of any form in the past few years.
Objective: To understand their profile, borrowing habits, interactions with bank or other financial institutions,
satisfaction with the loan disbursement process and even a short psychographic profiling.
Approach:
 Performed exploration and cross tabulation to bring insights of variables
 Performed regression to find the hierarchy of importance of given the attributes in driving Overall Customer
Satisfaction
 Performed Factor Analysis to club given parameters into a lesser number of factors and named the factors
based on the customer psychograph
Tools: R
Model building for prediction of Diabetes using R
Problem: A model is to be built which will lower the total cost of misclassification of the test dataset.
Objective: To predict diabetes based on the Custom Diabetes Dataset.
Approach:
 The Custom Diabetes Dataset is broken into 2 parts – Test and Training.
 The model is built on the Train dataset and tested on the Test Dataset.
 Cross validation (5 fold) has been performed subsequently. Cohen’s Kappa is calculated.
 Confusion Matrix is found out to determine the actual and predicted values.
 A graph is plotted which shows the effectiveness of the model.
Tools: Excel, R
Data Analysis for telecom dataset to improve client revenue using R
Problem Telecom Company wants to find out how to improve Revenue. The dataset has been provided to us. We now
need to dig deep to find out the interrelationships between variables, how is the revenue varying, which variables are
impacting revenue, etc.
Objective: Provide insights which will help in revenue maximization of client.
Approach:
 Education wise, Income wise, Age wise, Customer Category wise, Gender wise and Tenure wise explorations
are performed on the data.
 Data explored to find out how revenue is getting affected by the above groupings.
 Data analysis to find the Churn rate.
Tools: Excel, R
ACTIVITIES AND INTEREST
Conducted training session on Biometric Implementation and its usage at CMC Limited
TRAININGS AND CERTIFICATIONS
 Analytics for beginners from Jigsaw Academy
 Data Science with SAS from Jigsaw Academy
 TCS ascent training on project management and leadership skill
TOTAL WORK EXPERIENCE (5 YEARS 9 MONTHS)
Company Name: CMC LIMITED Designation: IT Engineer Duration: Sept, 2010 to Sept, 2015
Responsibilities
 Project Management related activities like Project Creation, Milestone creation and billing.
 Quarterly review with client and maintaining MOM.
 Vendor Management and monthly review meeting with vendor.
 Managing service desk and ticket driven process to resolve issues within agreed SLA.

2.  Escalation of issue on time to maintain customer satisfaction and commitment.
 Implementation Support for Oracle virtual machine Server
 IBM Genero Developer
 Server Administrator for HP Non-Stop Server, Fujitsu HPC
 L2 Network Support
Learning
 Project creation, cost sheet preparation, Vendor Management and Negotiation, Client Escalation Management,
SLA adherence
 Installation of HP MSA 2040; installation of OVM Manager on Test and Production Servers, creation of guest VM
from OVM Manager. Installation, Configuration, Multi-pathing in Database Server
Company Name: TATA CONSULTANCY SERVICES LIMITED Designation: System Engineer Duration: Oct, 2016 to Jun, 2016
Responsibilities
 Project Management related activities like Project Creation, Milestone creation and billing
 Vendor Management and monthly review meeting with vendor.
 Managing service desk and ticket driven process to resolve issues within agreed SLA.
 Escalation of issue on time to maintain customer satisfaction and commitment.
 Technical Support for FujitSu Primergy RX900