About

Shivendra is a highly skilled data scientist with over 7 years of relevant experience in the field. He is currently working as a Data Scientist at MoneyTap, where he has successfully built a customer acquisition scorecard using boosting methods. Shivendra has also used alternate data for new credit customers' scorecard using apps, location, device storage, and SMS data using NLP techniques. He has estimated the intent of customers for loans for better targeting, reducing Facebook campaigns CPA by 35% to INR 850. Shivendra has also predicted bounce status for EMI, 7 days prior to the due date, to define an action strategy to recover money beforehand and decrease loss rates. In his previous role as a Data Scientist at Intellicar, Shivendra analyzed time series data from ECU through OBD port and used neural networks for Vehicle Prognostics to prevent sudden vehicle breakdown. He applied machine learning algorithms for predictive modeling and driving fingerprinting related to automobile's performance. Shivendra worked with FORD India, Mahindra, and Ashok Leyland for better ECU calibration based on real-time and field data. He predicted the optimum gear state by using Hidden Markov Models and driver fingerprinting using Multilayer Perceptron's (MLP) for fleet owners (Zoom, OLA, UBER, TSRTC & Ashok Leyland). Shivendra was also an Assistant Manager at Bosch, where he was responsible for calibration of common rail diesel fuel injection systems. He processed and analyzed engine-related data of SUVs for ECU calibration and optimizing vehicle dynamics and performance. Shivendra performed predictive modeling for failure of fuel injection components and adaptive calibration of fuel injector based on time series data acquired from Bosch CCU. He worked extensively on Demand Control systems on Mahindra Scorpio project. Shivendra has a Master's degree in Computational Mechanics and a Bachelor of Technology in Mechanical Engineering from IIT. He also attended Puranchandra Vidhyaniketan Kanpur. Shivendra is proficient in various technologies, including Research Scientist, Data Scientist, ML, NLP, Flask, Python, Perceptron, Neural Networks, XGBoost, Scikit, Random Forest, Keras, Deep Learning, Spark, product designer, Pandas, Mobile, infra, and Apache Hive.