A Masters in Computer Science graduate from University of Southern California having deep interest in Machine Learning. Coursework on Machine Learning and Big Data Analytics at USC gave me a deeper insight about different classification and clustering techniques like Logistic Regression, Perceptron Learning, SVM, Neural Networks, EM and PCA algorithms. Various academic projects on different learning techniques gave me a practical experience on their usage. I feel well versed with Data Mining techniques and Natural Language Processing and can use Map-Reduce paradigm to extract data from large unstructured datasets.Further, an eighteen months of work experience in the industry and six months of research experience before start of my Masters program has helped me enhance my programming and analysis skills. I have been exposed to a myriad of people and working under two different setups has helped me become adaptable to different situations.Since the completion of my Masters, I have been working as a Data Scientist at Scry Analytics. My work involves developing algorithms and pipelines for solving complex similarity based problems, classification and regression problems for both structured and unstructured datasets. We work in the domains of finance, healthcare and internet of things.I believe that a lot of meaningful information can be obtained from the enormous data which is continuously growing. I aim to be a part of the research team working in the areas of data mining, information retrieval and machine learning and contribute in the cutting edge challenges.