• Machine Learning Engg./Data Analyst with 4 years of rich professional experience in Predictive Modeling/Machine Learning in Model creation, Model validation, Data Analysis and Data Reporting. • Created a strong Predictive model using Artificial Neural Network and Logistic Regression classifier for a European Union bank that identifies the customers vulnerability to churn in order to prepare a better retention program to retain the customers from the Bank. • Designed an analytical framework to segment the credit card transactions in to valid/fraud categories by implementing the Logistic Regression model to the data set which contains around 300,000 credit card transactions of a European Union Bank. • The implementation was done using the Python and the libraries like Pandas, Numpy, Seaborn, Keras/Tensorflow, Jupyter, Anaconda etc. • Evaluated the Model using statistical tools (Confusion Matrix, Precision/Recall Curve, Cross Validation (K-Fold), AUC/ROC curve and PSI ) for model validation based on the data provided by stake holders. • Proficient in reporting tools like SQL, SAS for data reporting, data analysis and data manipulation process. ©