I am a highly motivated and enthusiastic individual who tries to solve various problems through the power of data.
I am currently a graduate student at University of Washington, looking for full time positions in the field of Data Science and Analytics.
September 2016 - Present
GPA: 3.77
Coursework in Data Science, Machine Learning and Numerical Analysis
July 2012 - May 2016
GPA: 3.85
Coursework in Thermal Engineering and Numerical Modelling
Analyzed the effect of restaurant and eateries on Airbnb prices.
• Created a visualization tool using Folium mapping the listings and eateries on a map of NYC.
• Developed a machine learning model to predict the price of Airbnb listings based on various inputs.
Developed a program to predict music genre given a sound clip.
• Extracted important features using Singular Value Decomposition on 5 second audio clips.
• Trained the Model using Support Vector Machines to identify which genre the song belongs to.
• Achieved 80% accuracy using this classifier while identifying between 5 different music genres.
Identify temperature trends and predict temperature for 5 cities in the US.
• Performed ARIMA analysis to predict temperature for selected cities.
• Max, Min RMS error was 3.71 C obtained for Chicago, 2.1 C for LA for the predictions over 20 months.
Identified Enron employees more likely to have committed fraud.
• Tested various machine learning algorithms to identify Enron employees engaged in Fraud.
• Algorithms tested include decision trees, k-nearest neighbors, AdaBoost.
• Achieved a precision score of 41% and a recall score of 37%, higher than required.
Analyzed baseball data from 1871 to determine various patterns, identify top players and study relations between their performance and salaries.
Performed data munging techniques to clean data for Seattle, WA.
• Standardized various fields to make them searchable for different keywords.
• After cleaning, the XML data was imported and stored into MySQL database.
I enjoy data extraction, munging and cleaning in large datasets be it any format - JSON, XML, CSV...
Working with data to setup hypothesis and work towards proving/unproving them to learn new and interesting things about the data.
Use different regression, classification models along with time series modelling to predict future predictions from existing data.
Adept and comfortable in programming on C++, Python and Java, working with SQL and No SQL databases.
4105, Brooklyn Ave NE, Apt 101
Seattle, WA
98105 US
rjtgupta@uw.edu
Mobile: (+314) 295 3681
