Kaushik Shakkari is a graduate student at USC seeking a Master's degree in Computer Science with a focus on Data Science. He has work experience as a grader, team leader, and database intern. His research as an undergraduate focused on analyzing user browsing behavior. His skills include Python, Java, SQL, Tableau, Hadoop, and machine learning libraries. Some of his projects include clustering machines to detect malware, analyzing tablet sales data with Tableau, predicting customer churn for a bank, and optimizing plant growth recommendations. He has received awards for outstanding student and project contributions.

1. KAUSHIK SHAKKARI
#318, 2700 Ellendale Place, Los Angeles, CA 90007 | shakkari@usc.edu | +1 (213) 477-3601 | linkedin.com/in/kaushik-shakkari/
public.tableau.com/profile/kaushik3654#!/|github.com/kaushikData|datacamp.com/kaushikshakkari| kaushikshakkari.wixsite.com
EDUCATION
University of Southern California, Los Angeles, CA Aug 2018 - May 2020
Master of Science in Computer Science (Data Science)
Amrita University, Coimbatore, TN, India Aug 2014 - May 2018
B. Tech. in Computer Science and Engineering, CGPA: 9.18 / 10
SKILLS
Programming Languages Python, Java, C++, C, Scala, JavaScript
Storage Systems SQL, MySQL, Oracle DB, Cassandra, MongoDB, PostgreSQL
Visualization Tools Tableau, Plotly
Big Data Framework and Technologies Hadoop, Hive, Sqoop, Pig, Oozie
Libraries (Python) Scikit-learn, NLTK, Beautiful Soup, Urllib, Bokeh, Keras, TensorFlow
Cloud Computing Google Cloud Platform, VMware, Hyper-V
RESEARCH
UG Research Assistant, Amrita Multidimensional Data Analysis Lab, Amrita University, India Jan 2016 - Jul 2018
• Collaborated with Dr. Vidhya Balasubramanian, PhD, UCI, designed algorithm and created a tool ‘Lakshya’ to analyse user
behaviour while browsing Internet, detect the level of focus and nudge him back in real-time.
• Installed framework as an extension in several volunteers’ systems. Framework’s usage histories show framework detected
diversion and alerted user appropriately. Improved model accuracy to 95% through continuous feedback from users.
• Extrapolated insights on browsing behaviour with Plotly and Bokeh to make users understand their internet usage.
WORK EXPERIENCE
Grader for Analytics and Statistics (GSBA 537), University of Southern California Sept 2018
• Responsible for creating visualization and analytics assignments and grading student assignments on strict deadlines.
Team Leader, University Cisco collaboration real-time project Nov 2016 - Dec 2017
• Developed a generic big data framework using Hadoop for Rating and Billing Scheduling application.
• Automated scheduling of process execution via Oozie tool. Hive and Sqoop were used for data management and data transfer.
• Implemented code was reviewed, perfected, and pushed to production.
Database Intern, APTOnline Dec 2016 - Jan 2017
• Designed, modelled and optimized a set of DML operations and cursors in collaboration with Watershed Development Team for
Watershed Management Project (Andhra Pradesh State Government Project).
PROJECTS
Clustering machines and detecting anomalies to find malware affected machines Nov 2018
• Implemented PCA to reduce dataset to less than 40% of original dataset, retaining 95% of information.
• Executed various clustering algorithms like K-Means, Mean-Shift, DBSCAN, Agglomerative Hierarchical Clustering etc.
• Mathematically stated K-Means with K = 2 is best fit for dataset and detected anomalies (malware affected systems.)
• Used XGBoost, an implementation of gradient boosted decision tree to identify the most crucial features by F-Scores.
Analysing product and developing pricing and product strategies using Tableau Sept 2018 – Oct 2018
• Pre-processed and analysed sales data of tablets sold by different companies like Apple, Samsung, Kindle and others.
• Created a dashboard to show how Apple’s and Samsung’s products are competing in sales rank, rating and discount etc.
• Computed trend lines and dynamic plots for various features of each brand across week 1 to 24 and addressed outliers.
Predicting the customer churning and finding reasons for cancelation of bank’s term deposit Jan 2018 - Apr 2018
• Performed pre-processing by encoding data, dealing with null values and reducing dimension of dataset.
• Executed k-folded cross validation technique with ten splits to avoid overfitting of data.
• Computed accuracy for ten classification algorithms including multilayer perceptron, a feedforward artificial neural network and
adaptive boost and visualized data using seaborn and matplotlib libraries to find insights in data.
• Created an interactive visualization application using bokeh for analysing relations of features in dataset.
Data tidying and cleaning Gapminder Original Dataset Dec 2017 - Feb 2018
• Implemented data cleaning techniques like melting and pivoting for data to be ready for analysis.
• Performed preliminary quality diagnosis by assert statements and created five-dimensional plot in tableau.
OOLECA (Optimization of Live Space Using Computer Algorithms) - predicting the best plant that can be grown at the area
considering climate, groundwater, humidity and purpose for growing plant. Jul 2016 - Dec 2016
• Cleaned data from different data sources and designed the database schema for the application.
• Constructed hybrid (content-based and collaborative) recommendation system for users of application.
• Collaborated with environmental science department for designing survey and modelling application.
ACHIEVEMENTS AND AWARDS
Outstanding Student Award, Amrita University Apr 2018
Outstanding Contribution and Successful Project Delivery, Cisco, India Nov 2017
Achieved 4 badges from IBM for good scores in Data Science and Big Data (youracclaim.com/user/kaushik-shakkari)