The field of data science often delivers value in multiple ways to a business. One way is in the development of predictive data features such as personalization and recommendations, fraud detection and mitigation, home automation, self-driving cars, etc… Another common way is to drive decisions and insights within a company. For example, did the web or mobile feature you just released increase engagement?
Are we on track to make earnings this quarter? How about more operation-centric insights? Can we detect a complex failure pattern due to a new code release before it takes down our site? Data science can be used to build both internal and external solutions that drive a business. Come to this track to learn about recent innovations in this space that highlight full-stack data science solutions.
Souvik Ghosh is a Principal Staff Engineer and Scientist at LinkedIn. Before joining LinkedIn, Souvik worked at Yahoo! Research and as an Assistant Professor of Statistics at Columbia University. Souvik completed his PhD applied probability and statistics from Cornell University.
As an expert in probability, statistics and machine learning, Souvik has extensive experience in the research and development of large scale recommender systems. Souvik has numerous publications and patents and he regularly serves in the program committees of conferences like KDD, ICML, NeurIPS and CIKM.
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