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To Be A Data Scientist, You Must Be A Software Engineer: Antrixsh Gupta, Danalitic

Antrixsh Gupta is the CEO of and a Chief Data Scientist at Danalitic. He comes with vast experience solving real-world business problems in a variety of industries.

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“Apart from their mastery of technology and long-term vision, I treat business processes as programming challenges,” says Antrixsh Gupta, CEO & Chief Data Scientist at Danalitic

Analytics India Magazine caught up with Antrixsh to learn more about the research and data science industries in general. Antrixsh spoke on data science, its current state, and future predictions.

AIM: What drove you from senior software engineer to technical advisor to mentor to a researcher to CEO? Who or what encouraged you to pursue a career in data science?

Antrixsh Gupta: I was always fascinated by science and technology. I was always interested in knowing how it works. My ultimate goal was always to have my own company, develop new resources and make big profits. As I was fascinated with science and technology, I always wanted to work on new things and wishfully guide the learners. I would also say that some lucky breaks got me where I am today. I believe I had the ability to approach business processes like programming tasks apart from their understanding of technology and long-term vision. The variety of skills that I could learn along the way was one of the major reasons that encouraged me to pursue my career in data science. I was always interested in new market opportunities, and the skills in data science have helped me identify those patterns.

AIM: A researcher who became a CEO is an interesting metamorphosis. How did this transition take place?

Antrixsh Gupta: I would say that the transition wasn’t a piece of cake. As I already mentioned, honestly, my journey was paved with some lucky breaks. There were some personal motivations that took me from the lab to the boardroom. Being a CEO, you have to make loads of decisions without enough information, which could be challenging and here comes the role of the experiences you have had over the past years. I didn’t pay major attention to money; instead, I focused on my company’s developments and the journey I am onto. 

AIM: Is there a specific incident in your data science journey which you look back on with pride?

Antrixsh Gupta: This has happened to me very often, as I am involved myself in training and consulting and many times when my students call me and tell “Antrixsh, I interviewed your student”, and I feel very proud as both the interviewer and the interviewee are my students. And I must say, where we are now, it happened just because of my students. Also, when my students call me/text me that we got our dream job, it makes me very proud. 

AIM: It is great that being a machine learning facilitator, you have organized hackathons. You would have solved and witnessed various key challenges in the industry. Could you please share one of those interesting challenges with us? 

Antrixsh Gupta: Being ML facilitators, we conduct almost 50+ hackathons, and our main motive has been to conduct hackathons to help participants keep pursuing their goals. There are so many resources online and can sometimes be overwhelming, so helping participants choose wisely helps them develop their learning path individually, helping them by using hands-on projects on healthcare, retail, and the supply chain domain. It also helps the participants to gain domain knowledge by inviting industry experts.

AIM: What, in your opinion, is the most demanding area of research in the data science industry at the moment that requires attention?

Antrixsh Gupta: The healthcare sector represents one of the most important industries for data scientist involvement. Not only does an estimated 30 per cent of the world’s warehoused data come from the medical field, but the opportunities for improvement made possible by this cache could save the industry as much as $300 billion annually. Working in the healthcare industry as a data scientist means more than just efficiency improvements — it can mean lives saved. Because of this, data scientists are flocking to this humanitarian industry. 

AIM: What are your perspectives on the Indian data science industry’s growth? Could you share your insights with us?

Antrixsh Gupta: It is, without doubt, a highly growing industry. The hiring in this industry has increased by 45%, and there will be more than 10 million job openings in the coming five years. The impact of the data science sector is far-reaching, and as a result, a range of new roles and skillsets will be in demand. It is estimated that the industry is growing at a healthy rate. The industry is expected to grow seven times in the next seven years. Startups have also contributed significantly to the overall output in India.

AIM: Is India’s data science industry losing its competitive edge in terms of cost? With the cost of recruiting data scientists increasing, will businesses continue to outsource? What is your opinion?

Antrixsh Gupta: I would not say that the industry is losing its competitive edge in the country. Instead, data science applications have amassed all the industries and have readily increased the demand for data scientists. But the trends are changing nowadays. The demand is no longer the same as before. Even if there is a demand for data scientists, people lack either the skill set or the experience. Transitioning to data science is a smart move as it fetches far higher comparative returns. For the majority of businesses, outsourcing will be the right option as it will grant a high degree of flexibility and scalability. It will also lessen the burden of finding the right resources in a highly competitive industry.

AIM: In the industry, Who are your role models?

Antrixsh Gupta: Andrew Ng and Yann LeCun are two personalities that I look up to as role models in this industry. 

AIM: What are your favourite data science/AI books?

Antrixsh Gupta: These three count for my favourite:

  1. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World.
  2. Building Analytics Teams: Harnessing analytics and artificial intelligence for business improvement.
  3. The Data Detective: Ten Easy Rules to Make Sense of Statistics.

AIM: As a researcher and data science practitioner, what advice would you give to aspirants interested in pursuing a career in data science?

Antrixsh Gupta: My major piece of advice to the aspirants would be to start with practical projects and then slowly progress with theory. Ask questions till you become satisfied with your knowledge and tools. One can also find and join online communities that can help them learn and grow. Regularly read blogs, and listen to podcasts of industry experts. And for all the fresh minds, I would like to give one suggestion: before becoming a data scientist, you should first be a good software engineer. Don’t let yourself think you will be a master in a week or month, but a consistent approach to learning new things daily will definitely help you achieve your goal. 

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Picture of Dr. Nivash Jeevanandam

Dr. Nivash Jeevanandam

Nivash holds a doctorate in information technology and has been a research associate at a university and a development engineer in the IT industry. Data science and machine learning excite him.
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