Trained and optimized a RandomForest Classification model, to accurately predict item re-order, thus improving Sales by 22% for the next Quarter

• Helped improve targeted marketing for specific Retail Stores by Cluster Analysis using K-Means clustering and analyzing sales KPI’s.

❖ Highlighted ‘Red- Flags’ to C-suite executives using Tableau for intuitive Data Visualization.

• Modelled Classifiers in Python Scikit-Learn to compare accuracy in Predicting emotional sentiment from Brainwave readings.

❖ Used RandomForest, Logistic Regression, XGBoost, and Support Vector Machines classifiers

➢ Integrated Asset Classification: ❖ Analyzed and validated MorningStar and IDC vendor raw data for Asset Classification as per Business Rules for downstream modelling applications. ❖ Used efficient, and eloquent SQL queries to extract data.

New Item Demand Prediction: ❖ Currently working on a Recurrent Neural Network using Python for Demand Prediction model. ❖ Modelled an ELM Neural Network in R for Demand prediction of Fashion shoes helping Supply Chain Optimization and reduce overall stock.