Kaushik Kompella is a data science student seeking to explore big data. He has experience leading analytics projects and creating executive reports. His skills include Python, R, Hadoop, Tableau, and he has developed recommender systems and analyzed airline performance data. Currently he is a project lead for a nonprofit and has received several honors for his work.

1. KOMPELLA KAUSHIK
901, Apt #1002, S. Ashland Ave, Chicago, IL – 60607 (312)-871-8673, kkompe2@uic.edu
SUMMARY
 A data science enthusiast who wants to explore uncharted territories of big data
 Experience leadinganalyticsprojectsusingandcreating executive level reportsbasedonfindings
SKILL SET
 Statistical Software:RapidMiner,Python,R,Hadoop,MapReduce,SASEnterprise Miner
 Basic Programming: C, Java, html,SQLServer,MySQL
 Data Visualization:Tableau
EDUCATION
Masterof Science inBusinessAnalytics Expected12/2017
Universityof Illinois atChicago–LiautaudGraduate School of Business
Bachelorof TechnologyinComputerScience Engineering,GPA-3.72/4.00 06/2014
Jawaharlal NehruTechnological University–Hyderabad,India
EXPERIENCE
Business& MarketingAnalyst,Co-Founder–Valmore.in –Hyderabad,India 06/2014-12/2014
 Createda platformforstudentcommunity togetupdatedaboutvariousoffersand events
 Analyzedbusiness requirementsfordevelopingandmarketingthe product
 Managed A-Zinthe start-upwithmore stresson customerandmarketinganalytics
AssistantSystemsEngineer–TATA ConsultancyServicesLtd – Hyderabad,India 12/2014-06/2016
 Led the automation team of 15 and developed automation scripts for a healthcare project
 Prepared Return of Investment which saved 85% efforts for automation execution over manual
 Exposed to Software Testing process with various Life cycle models like Agile
ACADEMICPROJECTS
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 Movie RecommenderSystem:Ledateamof 3 graduate students todevelopandanalyze a movie
recommender system based on a data set consisting of over 100,000 ratings from around 1000
users and 1700 movies.Evaluated the performance using collaborative filtering algorithms like
Matrix Factorization for predicting ratings. Movies with high ratings were recommended to a
user. Reduced RMSE by 22% compared to the state of the art. Tool used: RapidMiner
 Analyses of Airline’s On-Time Performance: Led a team of 8 to effectively perform exploratory
analysis and present a visualization of American Airlines on-time performance metrics &
performance withrespect toothercompetitorsusing Bureauof TransportationStatistics dataset
containing more than 1 million rows & 147 variables for the year 2015-2016. Tool used: Tableau
 Target Fund Raising: Developed a classification model for a national veteran’s organization to
improve the cost effectivenessof theirdirectmarketingcampaignand capture potential donors.
Technique - Cleaned the data set containing around 500 attributes and 10,000 data points.
Reduced the dimensions in the data using PCA. Selected final set of variables using Random
Forestsvariable importance techniques.Appliedmachine learningalgorithms likeDecisionTrees,
Logistic Regression, Naïve Bayes, Gradient Boosting, and SVM’s to build the model
LEADERSHIP
 ProjectLead – InkindConsulting- RyanBanksAcademy (Non-Profit) - Chicago 09/2016-Current
 Vice-President–TCS WaverockToastmastersClub, HyderabadIndia 07/2015-07/2016
HONORS and CERTIFICATIONS
 Got selectedandwonthe best“ProductDesignandBusinessModel”presentationatthe
prestigious IndianInstitute ofTechnology,Madras inthe year2013
 WorldRank 1 inHackerankPythonchallenge
 Certifiedin DataDriven DecisionMaking fromPwC and Coursera
 Won the Humorous Speechcontestconductedby Toastmasters Public SpeakingGroupin 2015
 National Record Holderfor doingthe largestcube art with8000 Rubik’s Cubes