Building a successful career in the field of data science needs a lot more than just a thorough understanding of the various machine learning models. One has to also undergo a paradigm shift with regards to how s/he would typically approach any technical problems. In particular, patterns and insights unearthed from the data analysis have to be the guiding North Star for the next best action rather than the path of action implied by the data scientist’s or his/her superior’s intuition alone.
I will begin the talk by providing a quick overview of how the academic and industrial research in data science has evolved in the recent past and its implications on the business side, in particular the centrality accorded by businesses to ‘data-driven-decisioning’. I will then present a framework for translating a business problem into a data-driven technical problem and contrast it with the traditional way of software development. The framework includes addressing issues like: (a) availability of the right data at the right granularity, (b) interpreting the insights in the context of the data-biases, and (c) systematically merging human-expert’s inputs with the purely-data-driven-decisions.
Dr. Om Deshmukh is the CEO of TildeHat: a deep-tech start-up focused on recruitment analytics.
Om has a Ph.D. in Machine Learning from University of Maryland, College Park. Om has 50+ international publications (several best paper awards) and 50+ patents (filed/granted). In 2017, he was recognized as one of the top 10 data scientists in India.
He spent close to a decade in IBM Research and Xerox Research driving various state-of-the-art Machine Learning initiatives for global technical research, technology strategy and start-up partnerships. Om ran the delivery of data-science driven products at Yodlee Infotech for 3+ years before starting his entrepreneurial journey in Nov-2019.
Om is a well-known Machine Learning and Data Sciences authority in industry and academia, with several collaborations across IISc / IITs. Om is also an adjunct faculty at the International School of Engineering (INSOFE).