Expert Talks with Maavrus | Analytics, AI and Transformation

In conversation with Mamta A Rajnayak, VP & Head of AI-ML Products & Platforms @AI Labs, American Express | Expert Talks - 11

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“Do away with the Superwoman syndrome because what happens is in our own heads we keep thinking, oh, I am expected to be a superwoman. I'm expected to do well on the job and I'm expected to do well at home. I would say don't do that to yourself. Do a fair share of work at home. Do a fair share of work at the office. There is only so much that you will be able to do, but whatever you do, do a great job of it. And don't shy away asking for help.”  - Mamta Rajnayak’s advice to women professionals. Excerpt from the Expert Talks @MAAVRUS interview with her.


Today is Episode 11 of the Interview series on Expert-Talks, with Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Mamta Rajnayak VP - Head of AI-ML Products & Platforms@AI Labs , American Express. Prior to American Express, Mamta was managing Director and Retail Analytics Leader at Accenture Global AI Hub. Prior to Accenture, Mamta worked at Adobe, Evalueserve and ICICI Bank. Mamta holds 5 patents and is a frequent speaker at Analytics & AI industry forums.

 

Listeners will find Mamta’s perspectives very insightful and enriching. We are listing below, a few key points from the interview :

 

  • Mamta mentions that as a Senior Analytics Leader, apart from coming up with the right framework and bringing the right team on board - who will be able to deliver the work well,  one should also be able to understand stakeholder psychology and where they are coming from, address their concerns in an amicable manner, so as to get solutions implemented. Having said that, she also believes that solid technical skills are a must-have because that's why one is there in the first place. It is also important to understand the business problem at hand and frame it in such a way that the data would be able to solve it.

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    • For a project to be successful, it is important to develop a stakeholder power map. Understand who are the decision makers and what are their priorities. For eg, a Fraud Prevention Leader or Risk Assessment Leader would be more mindful of accuracy levels and may not be time-pressured, whereas a marketing leader may be okay with lesser levels of accuracy, but may want quick turnaround iterative inputs. Getting this clarity during the project planning stage can significantly enhance the chances of success.

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      • Any progressive organization should have an external perspective at the centre of its decision-making. You have to understand how the industry is progressing, where the movement is, and if,  growth in a certain technology is going to benefit you or not. Today there are multiple external data sources; you can use data from Google for eg search history of a person,  location data mobility data, credit ratings/scores from 3rd party data providers, and census/survey data.  You could also try collaborations with other different businesses.

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        • Low Code/no-code platforms will help analysts and data scientists be more efficient and free them of tasks that are repetitive and which can be automated. This will mean that the analytics teams will have a lot more time to engage with and understand the business, think more creatively and innovatively, and focus on implementing the solution practically in the business.  However, Data scientists and analysts will always need to have critical thinking skills and an understanding of data sciences from first principles.
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          Expert Talks with Maavrus | Analytics, AI and TransformationBy Maavrus