1. Used Classification Techniques like Random Forest & XGBoost, to find the variables that separate high performers from low performers among sales employees 2. Utilized Logistic Regression & Gradient Boost to predict the probability of an employee quitting the organization 3. Developed Power BI based visualization solutions covering Marketing, Supply Chain, HR datasets4. Performed Exploratory Data Analysis, Hypothesis Testing, ANOVA etc. to derive insights from underlying data

1. Designed Power BI based data visualization solution which helped management to get real-time information about the B2B customer segments 2. Used tree-based models like, Random Forest, Gradient Boost to predict the customer churn and find the factors responsible for it thus, resulting in more customer retention 3. Applied Time Series based ETS/ARIMA models to predict the monthly average balance, month end balance for the Govt. Banking

1. Understood Client Requirements and mapped client requirements to the interfaces and providing effective solutions2. Played key role in conversion of Functional Design Specification to Technical Design Specification document3. Monitored the overall functioning of the interfaces, identifying improvement areas and implement adequate measures to maximize customer satisfaction level