Suman Kumari

Explored the relationship between Demographic Factors and Customer Behaviour in Retail using Exploratory Data Analysis in Python; Forecasted customer demand for a leading smart-phone manufacturer's portfolio using time series analysis and linear regression in Python, SQL and Excel; Analyzed daily transactions in a retail store and tracked the customers spread across various locations along with the purchases/returns for different categories, using Python; Analysed claims data of insurance sector using logistic regression to detect frauds using Python – numpy, pandas; Performed customer analytics for E-commerce company on transaction data to understand the customer churn using classification model in Python-numpy, pandas, scipy, sklearn, statsmodel; Analysed the impact of bank marketing campaign on the term deposits using various ML algorithms - logistic, KNN, Random Forest, XGBoost, SVC; Developed probability of default (PD) model for retail portfolios of a US based banking client using logistic regression in python; Analysed the key factors for loan eligibility of customers for an Indian bank in Python using different ML algorithms - Decision Tree, Ensemble model; Time series analysis for demand forecasting for an automobile manufacturer using ARIMA, SARIMA and Regression techniques in python.