Nachiket Doke Resume
Published on: Mar 3, 2016
Transcripts - Nachiket Doke Resume
Phone: 980-267-8031 9309 Kittansett DR H, Charlotte, North Carolina email@example.com
University of North Carolina, at Charlotte Aug, 2014 – Dec, 2015
Master of Science in Computer Science
Terna, Mumbai University, India Aug, 2006 – May, 2010
Bachelor of Engineering in Electronics & Telecommunication
Algorithms & data structures • Cloud computing • Android development
Knowledge disc. & data mining • Database systems • Visual analytics
Android, Haskell, Prolog, Lisp, Python, R.
Frame Works: JUnit, jQuery.
Oracle, MySQL, Quantum, SPSS, Hadoop, Tableau, Hive,
Operating Platform: UNIX, LINUX, Windows
Applications: Eclipse IDE 3.4+, Apache Tomcat, GIT, Matlab, Maven, WEKA.
Analytics Executive (data analysis, warehousing, mining), IMRB, India May, 2011 - June, 2014
Projects at IMRB
Training – Quantum, SPSS @ IMRB, Dadar, India.
Worked on data of various FMCG players from categories such as agro based products,
face care products & hair care products also durable products such as cameras, automobile
Coding in Quantum & SPSS to build databases. Checking the built database.
Communicating with the data vendor regarding the type of data required.
Communicating with the researcher and delivering them the final data.
Auction website Spring 2015
Built an auction website on which people can post their items as well as place bids for the items
which they are interested in.
Front end was done using HTML 5 and angularjs.
Backend was done using java and ajax calls.
Internship portal Spring 2015
Built an internship portal on which students could register and add their skills.
The students could be given internship interview calls considering their skill set and choices.
The portal was built using PHP and MySQL was used in back end.
Image searching app Spring 2015
The app searched for images for an entered key using Flicker API.
Both XML SAX parser was used to parse the data.
The user was also able to mark his favorite images which were stored in a SQL database, to be
recovered the next time the same search was made.
To do app Spring 2015
Using this app the user could add to do activities, to remember them.
The use could create his own login credentials on the app using parse.com.
Parse.com was also used to verify the details while logging in.
The To do details were also stored on parse.com on the user’s account.
The date and time picker were also used to set the time for the activity.
Restaurant searching app Spring 2015
This app helped the user to search restaurant in a person’s locality.
Google map fragment was used for the same purpose.
It uses Google geocoding api to retrieve the information of the nearby restaurants.
Phone book app Spring 2015
Using this app the user could store the contact details of other people on his phone.
Jquery and Jquery mobile were used to build this app.
Cordova library was used to implement the functionality.
Selection game Spring 2015
In this game a user had to select certain number of a given fruit to complete the game.
The type and number of fruits appearing each time was decided by random selection.
The game ended in case of a wrong selection.
NPR app Spring 2015
In this app NPR api was used to display the load and display the stories on NPR.
The user could select the topic which he is interested in to get the stories related to that.
The user could also add stories to favorites.
iTunes app Spring 2015
In this app the itunes api was used.
Login and user creation was done using parse.com.
The user could get list of the apps downloaded from the api. The list could also be downloaded from
the favorites list that he saved.
Shark attacks in North Carolina Summer 2015
Collected data on various attributes such as weather, sea salinity, aquatic flora count, etc. from the
Collated the data together on the basis of date and mined it using the WEKA, to find the reason for
the surge in Shark attacks on the sea shores on North Carolina.
Election poll projection Fall 2015
Collected data of different pollsters and their rating from Github.
Cleaned the data and preprocessed it based on various criteria, such as grade and accuracy of a
Ran Naïve Bayes algorithm using Hadoop Map Reduce on the data to find the probability of
democrat or republican win in all the 34 states where there are going to be senate elections in 2016.
Confirmed our results with the data and result of 2012 elections, found our results to be 82% accurate
on the 2012 election data.