Kaushali Kundu is seeking a position that provides challenges and opportunities for growth. She has 1 year 3 months of experience as a business analyst. She is Lean Six Sigma trained and certified with strong analytical and problem solving skills. She has worked on projects forecasting the aviation industry and engine shop visits. Currently, she is working on a project analyzing gas turbine compressor efficiency and a market research project identifying new aircraft customers. She has a Master's degree in Statistics from IIT Kanpur and seeks opportunities in time series analysis, regression, and statistical inference.
Predictive analytics of students' academic performance can help decision makers take appropriate actions at the right moment and plan appropriate training in order to improve the student’s success rate.
Complete Introduction to Business Data AnalysisSam Dias
Beginner course on Business data analysis will help users breakdown the different techniques of data analysis with ease. As an entrepreneur or a business man or even a manager, you need to know data. Data plays an important role when it comes to making decisions about your business.
Introduction to the implementation of Data Science projects in organizations, with a practice session on how to apply machine-learning techniques to a business problem.
Notebook of the practice session is available at https://github.com/klinamen/ds0-experimenting-with-data
Predictive analytics of students' academic performance can help decision makers take appropriate actions at the right moment and plan appropriate training in order to improve the student’s success rate.
Complete Introduction to Business Data AnalysisSam Dias
Beginner course on Business data analysis will help users breakdown the different techniques of data analysis with ease. As an entrepreneur or a business man or even a manager, you need to know data. Data plays an important role when it comes to making decisions about your business.
Introduction to the implementation of Data Science projects in organizations, with a practice session on how to apply machine-learning techniques to a business problem.
Notebook of the practice session is available at https://github.com/klinamen/ds0-experimenting-with-data
The recruitment of new personnel is one of the most essential business processes which affect the quality of human capital within any company. It is highly essential for the companies to ensure the recruitment of right talent to maintain a competitive edge over the others in the
market. However IT companies often face a problem while recruiting new people for their ongoing projects due to lack of a proper framework that defines a criteria for the selection process. In this paper we aim to develop a framework that would allow any project manager to
take the right decision for selecting new talent by correlating performance parameters with the
other domain-specific attributes of the candidates. Also, another important motivation behind this project is to check the validity of the selection procedure often followed by various big companies in both public and private sectors which focus only on academic scores, GPA/grades
of students from colleges and otheracademic backgrounds. We test if such a decision will produce optimal results in the industry or is there a need for change that offers a more holistic approach to recruitment of new talent in the software companies. The scope of this work extends beyond the IT domain and a similar procedure can be adopted to develop a recruitment
framework in other fields as well. Data-mining techniques provide useful information from the historical projects depending on which the hiring-manager can make decisions for recruiting high-quality workforce. This study aims to bridge this hiatus by developing a data-mining
framework based on an ensemble-learning technique to refocus on the criteria for personnel selection. The results from this research clearly demonstrated that there is a need to refocus on the selection-criteria for quality objectives.
An analytics professional with over six years of experience in Data and Predictive Analytics modeling across various industry verticals, including banking, retail, FMCG and telecommunications clients.
Seeking a challenging position to utilize my quantitative and data interpretation skills complementing with my knowledge of Technology and Management to excel in areas of Analytics and Digital Marketing; which will nurture and bring forth the best I can offer to the organization, self & society
The recruitment of new personnel is one of the most essential business processes which affect the quality of
human capital within any company. It is highly essential for the companies to ensure the recruitment of
right talent to maintain a competitive edge over the others in the market. However IT companies often face
a problem while recruiting new people for their ongoing projects due to lack of a proper framework that
defines a criteria for the selection process. In this paper we aim to develop a framework that would allow
any project manager to take the right decision for selecting new talent by correlating performance
parameters with the other domain-specific attributes of the candidates. Also, another important motivation
behind this project is to check the validity of the selection procedure often followed by various big
companies in both public and private sectors which focus only on academic scores, GPA/grades of students
from colleges and other academic backgrounds. We test if such a decision will produce optimal results in
the industry or is there a need for change that offers a more holistic approach to recruitment of new talent
in the software companies. The scope of this work extends beyond the IT domain and a similar procedure
can be adopted to develop a recruitment framework in other fields as well. Data-mining techniques provide
useful information from the historical projects depending on which the hiring-manager can make decisions
for recruiting high-quality workforce. This study aims to bridge this hiatus by developing a data-mining
framework based on an ensemble-learning technique to refocus on the criteria for personnel selection. The
results from this research clearly demonstrated that there is a need to refocus on the selection-criteria for
quality objectives.
1. KAUSHALI KUNDU
Mobile: 09163807501 E-mail:kaushali423@gmail.com
Career Objective: To succeed in an environment of growth and excellence with challenges and self-
development, achieving personal as well as organizational goals.
Profile Summary:
A competent professional with 1 year 3 months of experience as BUSINESS ANALYST
Lean and Six Sigma trained and certified.
An effective communicator with strong analytical, logical thinking and problem solving
capabilities with leadership qualities as well as an excellent team-worker.
Good presentation skill with client handling abilities.
Organizational Experience: Since 23rd
June, 2014 with GENPACT, Kolkata.
Project Description:
1. Working as an active member in the forecasting team of Infrastructure, Manufacturing and
Sales. The major aim is to forecast the future scenario of the aviation industry with the
retirements and delivery numbers of the commercial aircrafts, in the long run, based on
historical data analysis, market research, statistical modeling like logarithmic regression, survival
curve (defined by client) ,rational thinking and business intelligence.
Software used: R, Ms-Excel, TM1(client provided)
2. Also working on the continuous improvement and up gradation of the existing forecasting tools
and methods in order to reduce the turnaround time of the process with increased efficiency.
3. Worked on an analytical project where the aim was to forecast the number of shop visits for
different engine models. Methods used are mainly: text-mining, K-means clustering, decision-
making (CART and CHAID), hypothesis testing and probability distribution techniques (Binomial
Distribution, used in this case).
Software used: R, Minitab, Ms-Excel
4. Currently, working as a member of the statistical project whose aim is to determine the thermal
efficiency (polytropic and isentropic) of the compressor of the gas turbine based on data points
on different internal factors like temperature ,pressure, rotation of the turbine. The primary
challenge is to handle the huge data provided along with data cleaning and missing value
imputation. Next step will be providing methods in order to improve this thermal efficiency.
Software used: SAS, Minitab
5. Presently, working on a market research project where the aim is to find target customers as
well as target regions where a new aircraft can be launched.
2. Technical skills:
Programming Language: C
Software : R, Minitab, Ms Office(Word, Power-Point, Excel), SAS(Basic)
Rewards and Recognition: Awarded Cheers Points (credits) 3 times for excellent performance and
extreme dedication in the forecasting team and other projects.
Educational Qualification:
Master of Statistics(M.Sc) from IIT, Kanpur (2012-2014) with CPI:9.2/10
Graduation(B.Sc) from St.Xaviers college, Kolkata(2009-12) with 83.8%( Hons)
Higher Secondary from Bidya Bharati Girls High School(2009) with 90.5%(best of five)
Madhyamik(Class x) from Bidya Bharati Girls High School(2007) with 92.6%
Areas of Interest: Time Series, Regression (Linear and Non-linear) analysis, statistical inference,
Clustering, Decision Making.
Summer Internship Projects: (May-July,2013)
Organization: Institute For Development and Research in Banking
Technology(IDRBT),Hyderabad
Project Title:
i) Comparison of Four Network Monitoring Tools
ii) Analysis of ATM and POS transaction
Areas Covered: Non Parametric Tests, Data Analysis and Graphical Representation
Software used: Minitab, R
Academic Projects:
1) Project Title: Verifying Parrondo Paradox Using Simulation Method
Project Guide: Dr. S.S.Dhar, IIT Kanpur
Software used: R
2) Project Title: Examination of the Effect of Drug on Blood-Pressure Using Non Parametric Tests
Project Guide : Dr. Sarmistha Mitra ,IIT Kanpur
Software used: Minitab, R
3) Project Title: Survival of the Fittest
Project Guide : Dr. Shalabh ,IIT Kanpur
Areas Covered: Sample Survey, estimation, testing of hypothesis
4) Project Title: Non-Linear Regression
Project Guide : Dr. Debasis Kundu ,IIT Kanpur
Software used: Minitab, R
3. Academic Achievements:
Secured All India rank of 9 in the Joint admission test to M.Sc(JAM) for IITs,2012
Received Inspire scholarship for Higher education, Govt. of India.
Personal Details:
Date of Birth: 27th
February,1991
Language Proficiency: English, Hindi, Bengali
Address: 37,Nanda lal mitra lane,Kol-700040, West-Bengal
Personal Interest:
Listening to Music, playing badminton, table-tennis, reading books, painting and singing.