Analytical professional with technical knowledge and critical thinking skills to thrive in data-driven environments. Tackles challenges with positivity and drive to overcome problems .
The project aims to decrease the frequency of patients returning to the hospital shortly after discharge, enhancing patient outcomes, and reducing healthcare costs. Analyzed 130 hospitals over 10 years and used ML techniques, like random forest, to predict patients likely to be readmitted, primarily using Python
Ten years of RBI data on currency exchange rates, 2,430 observations, were analyzed using t copula and bb7 copula models to calculate daily value at risk at a 99% confidence interval, and VaR was found to be 1.36% This demonstrates proficiency in risk management, primarily using SQL, RStudio, and Python
Performed RFM analysis on 500,000 retail orders, segmenting 4,000 customers into three categories, employed logistic regression to identify key revenue drivers with an accuracy of 85 percent, and developed marketing strategies to boost business growth using ML techniques, primarily using SQL, Python, and Tableau
Performed sentiment analysis on 46,000 tweets to predict the Lok Sabha election winner in 2019, primarily using Python and Tableau
Class Representative:
(06/01/19-06/30/21)
Acted as the primary point of contact between students and faculty, ensuring smooth communication and issue resolution Assisted in organizing college events, guest lectures, and academic workshops
Drama Club Member:
(07/01/19-03/31/22)
Executive Member Student Council:
(07/01/19-03/31/22)