Author
Author: Dr. Subhabaha Pal (Guest Author)
Dr. Subhabaha Pal is acclaimed Data Science Professional and Educator with 17 years of Experience including Corporate and Teaching Experience. He was included in the list of “20 Most Prominent Data Science Academicians in India – 2018” published by India’s Premier Web Portal on Analytics and Data Science “Analytics India Magazine”. He also received award of “Most Supportive Faculty” from Data Science Society, Sofia, Bulgaria in 2018. Dr. Subhabaha Pal did his Ph.D. and M.Sc. in Statistics from the University of Calcutta and MBA from the ISBMA, Pune. He worked in several well-known organizations like Kuwait Petroleum Corporation and Manipal Global Education Services in his corporate stint as SAP Technical Lead. He had taught in several well-known institutes like Manipal Academy of Higher Education (Manipal), International Institute of Digital Technologies (Tirupati), T.A. Pai Management Institute (TAPMI-Manipal), Sikkim Manipal University (Gangtok) and Manipal Academy of Data Science (Bengaluru) in his academic stint. He also served as consultant in several organizations like CALINFO Gurgaon (IT Services), Zarachy Canada Ltd.-Canada (Metallurgy), Payopa Healthcare Bengaluru (Healthcare) and Superior Informatics Ltd.-USA (Homestat – IT and Analytics Services).
Dr. Subhabaha Pal had published 44 research papers till now in reputed indexed journals and also published 3 books in reputed publishers like New Age Publishers Pvt. Ltd. (Erstwhile, Wiley Eastern) and Manipal Press. Currently, he is authoring a book on ‘Analytics in Business Operations using Machine Learning, R and Python’ in CRC Press (Taylor and Francis Group). He also co-founded an Analytics Services Company InstaDataHelp Analytics Services ( www.instadatahelp.com ) along with his wife.
Dr. Subhabaha Pal’s areas of expertise includes Data Science and Analytics, Machine Learning, Deep Learning, Econometrics and Information Systems. The courses and tools he taught in different institutes include Data Science, Data Analytics using ML, Statistics, Econometrics, Research Methodology, Marketing Analytics, Financial Analytics, Exploratory Data Analysis, R, Python, Tableau, SAS, Rapidminer, SPSS and STATA.