In conversation with Mathangi Sri Ramachandran, Chief Data Officer, YUBI | 18

For a long time in the industry, I think we made the mistake of going behind people who were experts in let's say certain set of algorithms; who understood the math very well, but they were not able to convert that mathematical problem or match the mathematical problem to a business context. So without context, they are just algorithms and numbers and libraries and codes which may or may not solve the actual business problem– Excerpt from the interview with Mathangi Sri Ramachandran.  Today is Episode 18 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Mathangi Sri Ramachandran, Chief Data Officer at YUBI.  Before YUBI, Mathangi headed Data Science functions at GoFood ( part of GoJek ) and PhonePe.  She has near 20 years of experience in Data science and analytics, 100+ patents to her name, is an author of 2 books and is among the Top 50 Influential AI leaders in India.   We are listing below a few key points from the interview : Data is an organisation’s asset. So if data access gets restricted to only the data science and analytics team, then democratization and large-scale data-driven decision-making will not happen. So depending on how friendly the end users are with technology, you build an application layer and democratize these components so that each can explore their insights. In a simplified manner, Mathangi brackets analytics initiatives into  1. Human-led and Machine-assisted, where you provide self-serve models and data access in intelligent formats to businesses,  for them to make decisions and act quickly and 2. Machine-Led and Human-governed, where the analytics team is building transformative break-through models, with high and long-term business impact. For the Data Science team to create a meaningful impact in an organisation, the pre-requisites are the Quantum of available data, Business problems with constraints and an Organisation culture that encourages experimentation. An organisation that is open to experimentation & failure, will encourage teams to explore probabilistic scenarios and take big bets for non-linear impact. The absence of this can lead teams to be more deterministic in their approach, which by nature will be incremental in impact.  You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

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