As a Data Scientist at Nationwide, I develop machine learning models to price new insurance policies based on the risk of a home. I use advanced techniques such as BBC-CV, multi-criteria stratification, and GLM and Non-GLM models to improve the prediction of high loss homes by 28% compared to benchmarked actuarial models.I have a Master's degree in Computer Engineering from Arizona State University, specializing in Artificial Intelligence and Robotics. I published a paper in the International Journal of Procedia Computer Science on a new method for vehicle detection based on color intensity segregation, which achieved 90% detection rate and reduced computational load for real-time applications. I also received a product development fund and a prize money for my "Smart Bus Transportation App" in the Texas Instruments: Indian Innovation Challenge Design Competition. I am skilled in Python, R, SQL, OpenCV, TensorFlow, PyTorch, Caffe, ROS, AWS, Git, Jira, Spark, Hadoop, Anaconda, PostgresSQL, and MySQL. I have completed courses on Machine Learning, Image Processing, Foundations of Algorithms, NLP, RL, Data Mining, and AI & Robotics. I am interested in a career related to machine learning, where I can apply my knowledge and experience to solve real-world problems and create value for the society.