About

Vanshika Raj is a highly skilled Machine Learning Engineer with a passion for data analysis and research. With over 2 years of experience in the field of data analysis, Vanshika has developed a strong analytical thinking ability that has been instrumental in driving various initiatives. She possesses great interest in Machine Learning research and has worked on several projects in this field. Vanshika's experience in software development in a banking project has equipped her with a great knowledge of data and its behavior. She is currently working as a Machine Learning Engineer at Quantiphi and is also a Mentor at Almabetter. Her expertise in ML, XGBoost, NLP, Deep Learning, Hyperparameter, Random Forest, ETL, Python, Big Data, AI, Data Scientist, Research Scientist, Software Engineer, SQL, Search, GCP, Computer Vision, TensorFlow, AWS, BERT, SVM, Keras, Kubernetes, Docker, DevOps, and Pytorch makes her a valuable asset to any organization. Vanshika has a Bachelor of Technology degree in Electronics and Instrumentation from Techno India and completed her higher secondary education from DAV Public School, Patna. She has worked as a Data Analyst at TCS, where she developed and tested extraction, transformation, and load (ETL) processes, designed and developed Informatica Mappings and Sessions based on business user requirements. Vanshika has worked on several projects, including the development of a model for Loan Default Prediction using Machine Learning Technique, where she developed an XGBoost based binary classification model to predict whether a customer will default on a loan. She also developed a model for Transport Demand Prediction using Machine Learning technique, where she used Linear, Decision Tree Regressor, Random Forrest regressor, and XGBoost to predict the number of tickets that would be sold by redBus for the rides which end in Delhi from 14 adjacent places. With a relevant experience of 3.78 years, Vanshika is a dedicated and hardworking professional who is always eager to learn and explore new technologies. Her passion for data analysis and research, combined with her strong analytical thinking ability, makes her a valuable asset to any organization.