Welcome to another episode of Leading with Data! This episode is all about Mathangi Sri Ramachandran, a data science leader with over 19 years of experience. Renowned for her work in building cutting-edge solutions and high-performing teams, Mathangi’s insights will illuminate the evolving landscape of data science and AI, not just in boardrooms but for everyone interested in this exciting field. Let’s dive in and discover what’s happening in the Data world with Mathangi!
You can listen to this episode of Leading with Data on popular platforms like Spotify, Google Podcasts, and Apple. Pick your favorite to enjoy the insightful content!
Now, let’s look at the details of our conversation with Mathangi Sri Ramachandran!
In my two decades of experience, I’ve witnessed a monumental shift in the perception of data science. Initially, data was seen as a tool for static analysis, but today, it’s a game-changer in decision-making. Boardroom conversations have become AI-oriented, with AI no longer just getting a seat at the table but being a central topic of discussion. The potential of AI is immense, and we’re just beginning to scratch the surface. We’ve moved from human-led, data-assisted decision-making to AI-led, human-governed processes, which is a significant transformation.
The core principles of any job remain the same: sincerity, passion, and hard work. Transitioning from statistics to machine learning and AI was a learning curve, but my ability to read and understand data helped me adapt. I learned by doing, by being part of a team, and by practicing coding, which has always been a stress buster for me. The stress of continuous learning in technology is real, and it’s crucial to stay updated to do justice to your profession and the people you work with.
Writing books was a way for me to deepen my understanding of the field. My first book on text mining was about solidifying my knowledge in a structured way. The second book aimed to bridge the gap for non-data science professionals who engage with data science for critical decisions. It’s about setting the right expectations and understanding that data science is not just about engineering or business; it’s a blend that requires a deep understanding of data, machine learning foundations, and the ability to integrate data science into mainstream business.
At YUBI, we’re building a robust lending infrastructure that results in financial inclusion. My role spans from data instrumentation to data governance. We’ve mapped AI across the customer’s lending journey, from underwriting scores to document parsing using NLP and vision, to monitoring signals post-disbursement, and optimizing collections strategies. We’re leveraging AI in vision, voice, text, and structured data, backed by a strong data management layer, to drive data through AI and achieve our vision of financial inclusion.
Generative AI will significantly impact two main areas in BFSI: funding loans and collecting them. We’re focusing on generating credit information reports using generative AI, which can revolutionize underwriting by providing detailed, multi-page financial summaries. In collections, we’re enhancing customer interactions through digital channels like SMS, IVR, and conversation engines in local languages. Generative AI will also transform document processing, marketing campaigns, and customer interactions in banks and insurance companies.
Diversity in AI is not just about filling quotas; it’s about accepting and accommodating different leadership styles. Organizations need to embrace psychological diversity and respect the diversity of thoughts. Women leaders should be unabashedly themselves and pave the way for more women to enter the workforce and ascend to leadership roles. It’s about creating an environment where diverse perspectives are valued and contribute to a healthy organization.
As we wrap up this insightful conversation with Mathangi Sri Ramachandran, it’s clear that data science and AI are on a journey of continuous transformation. The progress has been astounding, from its beginnings as a tool for analysis to its current role as a powerful force in shaping decisions, like detecting fraud in financial services. Mathangi’s invaluable insights shed light on AI’s transformative power and its critical role in shaping industries. As we explore data science further, let’s learn, adapt, and embrace diversity, just as Mathangi suggests.
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