Asha Vishwanathan leads the machine learning division at Verloop.io, a Conversational AI platform. Her expertise lies in NLP and computer vision and her career spans 15+ years. She got bitten by the data science bug in 2014 and made a pivot from analytics. “ML piqued my interest as it was the perfect blend of programming and data related technologies that I had been dealing with in my career,” said Asha.
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Analytics India Magazine spoke to Asha to understand her data science journey. “Disregarding your past experience and starting afresh is a challenge that one must overcome while transitioning between different job profiles,” she added.
Excerpts:
AIM: In spite of a successful career in analytics, what made you switch to the world of data science?
Asha Vishwanathan: After working for almost a decade with major IT brands, from corporates to budding startups, I took a sabbatical from work to explore my ‘Ikigai’ and went back to basics to understand what actually made sense to me. Upon realising I have an affinity towards programming, I moved to machine learning. Things got interesting when I took a course on data science through Coursera and my interest in the field developed.
AIM: How did you develop your data science skillset?
Asha Vishwanathan: I started with a lot of general reading on the basics. I started with research on business intelligence as it was something that I had worked on before. Having a background in business intelligence, data visualisation, reporting and dashboarding, I understood the nuances and found data science in this field to be a natural extension of what I had been doing. My own past experiences and understanding of the field guided me through the vast universe of data science. I started off by doing an introductory course through Coursera to gain a basic understanding of the field and later found a lot of online material. However, the online resources lacked a structured approach and one can easily get lost in the world of data science. Doing advanced courses on R and Big Data through Jigsaw gave me clarity on the path I wanted to take. In 2020, I did a business analytics course at the Indian Institute of Management, Bangalore which gave me a sweeping understanding of the data science scene.
AIM: How did you feel when Harvard Business Publishing chose your case study on skilling needs of the Indian ecosystem?
Asha Vishwanathan: The project was actually about identifying the skilling needs in the Indian ecosystem. The government provides a lot of schemes and initiatives to train and enable the common people. But, many drop out or are unable to complete such courses. We wanted to find out the root cause of this discontinuation and our research revealed that the skillset provided by the courses did not match the required job profiles. So we decided to look at building a system that would recommend the type of skills that the target audience needs for specific job profiles. It was a challenging process as many candidates were from a blue-collar segment and lacked a basic resume. Taking into account people from different backgrounds like coconut vendors, labourers, plumbers, etc., we created a model to predict the possibility of such individuals passing the aforementioned certifications using previous assessment data. We took data from soft skills required from the job, skills that the individuals have married them all in a comprehensive recommendation model that caught the eye of Harvard business publications.
AIM: When did your data science journey actually begin?
Asha Vishwanathan: I was already working in data science before joining IIMB. But I decided to do more to understand the breadth of the field. I soon realised that I have stumbled into a niche of machine learning while working in Kernel Insights. The road took many turns after I got certifications from Jigsaw and I joined a company called Poolcircle. There, I worked on changing the ride-sharing scene in Bengaluru using ML methodologies and data science. To change the way people commute, we looked into making a product that recommended routing strategies. After Poolcircle, I joined an early-stage startup called Kernal Insights where I tackled computer vision problems.
AIM: What kind of projects are you heading in Verloop.io?
Asha Vishwanathan: After joining Verloop.io, I tackled projects around NLP and conversational AI as I realised there are a lot of similarities between how the models work across computer vision. I faced challenges specific to chatbots, the whole ecosystem that it caters to and their implementation in typical B2B, SaaS type models. Working on the hosting and deployment of such models is especially interesting as it is not just restricted to machine learning algorithms but also about scaling up the project to meet industry standards. Looking for a solution from an end-to-end standpoint is what excites me the most.
AIM: What’s your advice for data aspirants?
Asha Vishwanathan: Data science is a detail-oriented and rigorous field. In order to make it in this market, you must get down to the basic principles and understand if it is their cup of tea. You should also be able to persevere through algorithms day after day and work on similar problems without being saturated. Don’t just blindly dive into it because it’s trending, you might not like it later.
