Shreekant Saurabh

Developing and Improving a Statistical Model to estimate Price Elasticity of Demand. Developed a web application using R-shiny for Price Strategy Simulation. Seasonal Demand Forecasting by using various time series techniques like ARIMA, VAR and Neural Network. Worked on Google Cloud platform for data extraction, storage and model deployment. Coordination with team of data engineers to make models deployment ready. Web scraping for competitor data.

Projects Implemented: - Employee’s expenses classification using NLP and Machine Learning Multi-level classifier. - Semi-Supervised Document classification using Natural Language Processing and LDA. - Human Resource Analytics on salary remuneration and gender pay gap statistical analysis. - Employee Time Recorder tool data analysis using Hypothesis Testing. - Optical Character Recognition of Hand-written & digital texts using Neural Network & Computer Vision API on Microsoft Azure.

Projects Implemented: - Apply Computer Vision and Convolutional Neural Network to automate the User Interface display panel appearance validation on HP printers. - Use Recurrent Neural Network and Natural Language Processing to auto generate the keywords to be used for Robot framework during validation tests development. - Bank Customer Segmentation using Decision Tree. - Customer Churn Behaviour using Decision Tree & Random Forest.

Projects Implemented: - Implemented Chatbot using Deep Learning & NLP for Vodafone’s technical support team. - Telecom Customer Churn Analysis using Decision Tree. - Customer’s Review Analysis using Natural Language Processing.