About

Suryanaman Chaube is an experienced research scientist with over 8 years of experience in data-driven and physics-based modelling techniques. He is currently working as a Principal Data Scientist at MakeMyTrip, where he is responsible for developing and implementing machine learning and deep learning models for various business applications. Suryanaman's major areas of interest include machine learning, deep learning, and computational materials science. He has a strong background in data science, software engineering, and predictive maintenance. He has worked on various projects related to healthcare claim adjudication, predictive analytics for furnace maintenance, and predictive maintenance for manufacturing companies. During his tenure at Abzooba, Suryanaman played a key role in developing ML models to identify incorrectly denied claims, which achieved an F1 score of over 0.8. He also developed a machine learning framework that utilizes physical and chemical properties of burden raw materials obtained from daily laboratory reports to predict the possibility of furnace hanging. Suryanaman has a dual degree in Metallurgical and Materials Engineering from IIT Madras. He has a strong technical background in Python, Scikit, Keras, Pandas, SQL, AWS, AI, Amazon Athena, SVM, Sagemaker, Databricks, CNN, Data Engineering, NLP, Spark, Big Data, and MySQL. Overall, Suryanaman has 9.62 years of relevant experience in the field of data science and predictive maintenance. He is a highly motivated and results-driven individual who is passionate about using data to solve complex business problems.