About

Naman Lal is a skilled Data Scientist with a passion for data analysis, modelling, and visualization using Python. With over 3.86 years of relevant experience, he has developed good data-driven problem-solving skills in classification/regression, time series, cluster analysis, and baseline deep-learning models. Naman is an active participant in online competitions like Kaggle, Hackerearth, and Analytics Vidya, where he has showcased his expertise in data science. Currently, he works as a Data Scientist at Games24x7, where he has been responsible for developing and implementing MCTS-based bots for Bubble Shooter games. He has also researched and implemented Bubble Shooter Simulator, using Python and Gym as his tech stack. Prior to joining Games24x7, Naman worked as an Associate Data Scientist at Oracle, where he designed and developed InterWorking Function (IWF), a networking function in 5G Network. He built this from scratch, implemented it in Spring Boot, J2EE, Drools Rule Engine, and deployed it using Kubernetes and Oracle Cloud. Naman has a Bachelor of Technology (B.Tech.) degree in Computer Science from the Indian Institute of Information Technology, Design, and Manufacturing, Jabalpur. He also completed a Nanodegree Program in Deep Learning from Udacity in 2021. Naman's tech stack includes Data Scientist, Research Scientist, AWS, Python, Reinforcement Learning, Computer Vision, Kubernetes, Mobile, ML, Naive Bayes, Software Engineer, Deep Learning, GAN, Test, Spring Boot, Spring, CNN, Stemming, OpenCV, Spark, Scikit, TensorFlow, Pandas, Neural Networks, iOS, and Pytorch. He is a Kaggle Competition Expert and is always seeking new challenges to further enhance his skills and knowledge in the field of data science.