- Worked on comparison of leading Mutual Fund houses on their performances across various sectors over past 5 years
- Analyzed associated Risk factor using parameters like sharpe ratio, alpha, beta, standard deviation
- Studied the impact of macroeconomic factors on the fund performances and compared the houses on their vulnerability
- Created a fuzzy model to assess mutual funds against their respective benchmarks using time series analysis
- Assigned ensembled scores to houses based on above criteria to finally declare best performer
- Performed Quantitative analysis based on the number of cardholders, number of Merchants and the number of ATMs in each area
- Implemented SOA (Strength, Opportunity, Aspiration) analysis technique for qualitative analysis of all three competitors
- Proposed a 2-stage scoring system by using zip codes demographics, influence of locality of ATMs on the number of transactions
- Built an interactive dashboard in Tableau to provide insights on key performance measures and fragrance attributes of the products
- Used logistic regression to predict the probabilities of liking of the products leading to identify the factors affecting the likability
- Used an ensemble vote of forward and backward stepwise selection method and information gain to identify 7 important features
- Improved the cross-validation AUC-ROC from 0.73 to 0.85 by creating new features from the existing features in the dataset