Nandish Madhu

Group Manager - IT, Intuit

Nandish has spent his last 19+ years in the IT industry, building and managing infrastructure for organizations ranging from services to retail and financial domains. Specialized in Networking, Nandish has covered the spectrum of all of the infrastructure domains and has been spending most of his time in Technical Leadership roles. Known to disrupt self for a better tomorrow, life has been going on for Nandish until he recently decided that incremental self-disruption wasn’t good enough and decided to venture into a tangential territory of Data Science and started his Masters program.

Apart from his core domain, Nandish also leads the DevOps community for the organization enabling a platform for engineers and leaders to learn, share and learn! He is passionate about exploring newer domains and believes that grey hairs, age or a title in our career shouldn’t be a barrier if we can commit to learning what we are passionate about! He enjoys sharing his experience and inspiring the fellow members through tech talks in the organization.

Nandish strongly believes that there is a need to bridge the gap between developers and non-developers that would lead to bigger and better outcomes for the organizations.

 

Talks on Wurreka:

AI/ML is no more a buzzword. It is now becoming an implicit expectation in every domain.

Few have latched on to this early in the game and few are contemplating if it is for them or not. Data Scientists are doing a lot of heavy lifting in this domain. In this presentation, I would like to share my point of view on what the “non Data Scientists” can potentially do in the field of AI/ML. Especially on enabling our colleagues in Product Development, Business Analysis, Sales, SREs, Development, Care and Security to be able to join the party!

Every individual can join the AI/ML party and operate in their capacity. Not everyone has to learn mathematics or complex algorithms or programming languages. We will talk about scenarios where a section of our friends might want to limit themselves to “creating business case”, few would want to understand “how stuff works”, few may want to try “hands-on” to get a feel of what is AI/ML and finally the ones who might want to seriously “go deep” into the technology. For each of these sections, we will talk about “what” and “how” they can join the rest in the organization in the AI/ML journey.

For example, in the case of a Care agent or a Developer who has access to customer behaviours, a business case could be to identify if the number of times a customer called care agents (that is recorded in CRM database) has any relevance to the same customer cancelling subscription (that is recorded in billing database). Coming up with such business cases itself would be value addition to the Data Scientists in the organization. If the Developer or the Care agent is interested in exploring further, could study the data and try his/her hands on the tools and technologies that are widely available in the data science forums. Ultimately, if one decides to master the art, there are avenues that we will touch upon as well in this talk.

The goal is to break the barriers and get everyone onto the first gear so that the vehicle can move. Depending on their interest and ability, people can get onto higher gears!

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