HAYAVADAN .G. NARGUND
H.No 322/A, 5th Cross, 5th Stage, Sachidananda Nagar, R R Nagar, Bangalore 560098
E-mail:-Mobile: -
Objective
Highly motivated post graduate in computer applications with 12 years academic
experience. Seeking to use strong quantitative and communication skills in a position
within the field of data analytics.
ANALYTICAL SKILLS & CERTIFICATIONS
Certification:
Analytics foundation & Data science with R - Jigsaw Academy, Bangalore
Wiley Jigsaw Certified Big Data Specialist -Jigsaw Academy, Bangalore
Fraud Analytics Course - Jigsaw Academy, Bangalore.
Analytical tools and Skills:
Language & Tools - R, Python Language, Rstudio, spyder, jupyter notebook, anaconda.
R Packages- cluster, stats, caret, factoextra, FactoMineR, gplots, ggplot2,
Statistical & Modeling Techniques
Regression Techniques – Linear | Logistic
Multivariate Analysis | Principal Component Methods | Data Visualization
Cluster Analysis | Decision Trees | Multicollinearity
Hypothesis Testing | ANOVA | Chi Square | Correlation
Cross-Tabulations | ARIMA time series forecasting.
Proprietary Object Oriented Programming Language – R, Python.
Understanding of business process in R | Python & Distribution.
MS Excel, Hadoop, MapReduce, Pig, Hive, Sqoop, Flume, RHadoop, Tableau & Prep.
Education
Master of Computer Application, Department of
ComputerScience, Karnatak University, Dharwad, Karnataka, India.
Educational Profile
Course
Institute
Dept OF Computer
Science Karnatak
M C A - 2007
University, Dharwad
M M Arts & Science
BA - Computer
Applications- 2004 college,Sirsi
JODC- 2001
M M Arts & Science
college Sirsi
University / Board
Karnatak University
Dharwad.
Aggregate
64.59%
Karnatak University
Dharwad.
69.21%
State Council Of
Vocational Education
67.19%
CASE STUDIES AND PROJECTS
Analytics projects.
1) CityMandi (http://www.citymandi.com) Company wants to mine the consumption data
of citymandi and perform analytics on diverse metrics like SKU based consumption,
Forecasting of consumption, and Inventory Forecasting. The company wants to estimate
the consumption for each item from each customer and forecast inventory for various
items. Specifically, in addition analytics on drop in demand from customers, and
suggestions on sales increase for each such customer across months is an important output.
Analytics on fast moving items, largest volume item, largest revenue fetching items etc.
Predictive and explorative techniques, Pareto analysis for figure out what could be the
most relevant product categories, Use different time series techniques such as time series
decomposition, Holt Winters and Arima models.
2) Store Clustering Objective of the study was to create clusters based on
certainparameters. There are 515 store spread across Tamil Nadu and Karnataka to
identify the buying behavior in these stores. K-Means Clustering technique used in R
to analyze data, create cluster profiles and provide recommendations based on cluster
profiles
3) Car Price Estimation Objective of the study was to run a regression model that
willexplain the price of a car as a function of different attributes. Linear Regression
modeling technique used in R to analyze and formulate the results.
4) Fraud Analysis of Loan Customers of a bank using logistic regression.
5) Worked on predictive modeling for the US thoroughbred Horse Racing Industry
withthe help of historic race data and taking into account various factors affecting the
earnings in horse races. Regression analysis was done to form a model so as to predict the
earnings in any given race in different conditions and tracks so as to maximize the
earnings and profits.
6) Email Marketing Campaign. The project is to Analyze email data fetched from a
Marketing email campaign of a magazine publisher. The High level design is fetching the
user behavior on the campaign email send to them and how they responded on this. Data
is in the form of csv file and its then moved to HDFS. All data transformation is done with
some pre-calculations. Reports are displayed on the dashboard CTOR by any field
provided by the client. And business rules are implemented for the report generation. e.g.
number of head count for per household. The exploratory data analysis and information
collected can help in predictions. Data preparation methods using PIG and then some Data
queries using Hive. End objective is to find which audience is interested in offer or not
with the email send.
Professional Experience
(1) Rajarajeswari College of EngineeringBangalore.
Designation : Asst.Professor
19/7/2010 TO till present
Responsibilities:
i.
Working as a full time Asst.Professor in the Dept. of MCA for 10.2 years
at RRCE.
ii.
Worked as a VTU flying squad Chairman and member.
iii. Worked as a External and Internal examiner for MCA Lab Examination.
iv. Handled subjects like – C, C++, CG, SP, ADA, JAVA, J2EE, UNIX, Python,
OOMD, NOSQL, Big Data Analytics, Machine Learning.
v.
Attended seminars, workshops and conferences.
vi. Placement training and transportation coordinator.
vii IBM certification for handling Rational Software and providing training.
viii Member of Indian Society For Technical Education (MISTE- LM69739).
ix. Serving as a Peer-Coach | Mentor to Students.
x.
Guided MCA projects and Evaluated.
xi. Worked as a VTU question paper setter for MCA.
xii. Worked as a resource person for conducting workshop.
(2) DayanandaSagar College of Engineering Bangalore.
Designation : Lecturer
21/7/2008 TO 20/2/2010
Responsibilities:
i.
Worked as a full time Lecturer in the Dept. of
MCA(VTU) for 1.7 years at DSCE.
ii.
Handled subjects like OOAD,OOMD,OR,C,C++.
iii.
In charge of Disciplinary committee.
iv.
Managing seminars, workshops and conferences.
Date:
Place:Bangalore
Your’s Faithfully
Hayavadan G. Nargund
