“Low Profile, High Growth” is the mantra we took from Bastin.

We had this enlightening and interesting conversation with Bastin Robin, Director of Decision Science, at CleverInsight. Robin has been recently honoured as one of the Top 20 conversational AI leaders by the Transformance Forum, 2022. His unique outlook made us even more excited to share his Pearls of Wisdom with you.

Bastin, tell us about your role as a Leader in your Job, also what does a day in your Profile look like?

• So, formally my designation is Director of Decision Science, but I would call myself a data practitioner, rather than using all these big words. Because I strongly believe data science is more of an evolving role. We are bound to learn new skills and since CleverInsight is a complete data science company where we start from Data Engineering and produce some actionable insights, we simultaneously focus on good Data Research because that keeps the progress streamlined.

Please share more about the Title Paradox where the love of being called a “Data Scientist” overpowers the Job description.

• That is true. In the limelight of all the fancy titles, we are missing out on understanding the role description and its associated limitations too. For example, for being called a Data Scientist being able to execute a machine learning program with a couple of libraries and building a few models will not be enough but the profile requires you to be a domain expert and must have a proficient field knowledge.
• Thus, I always emphasise being called a Data Practitioner and performing what type of work your role demands whether it is Data Processing, Domain consulting, Building Data Models and its deployment and maintenance. Sometimes we lose opportunities to be called a certain thing and not get to the crux of the job description and fail to become a complete Data professional, which I believe is the rock foundation for this umbrella concept of AI.

What started your love for Data? How has your profile transformed from where it started?

• This journey has been quite an unexpected one, as being a backbencher I at times did not love Maths as a subject. However one of my professors said that you are only a marginal engineer if you can’t code. So, I undertook one programming language and mastered it. In this process, I realised that you could develop and analyse anything if you are capable of coding.
• Around the same time, I was going through the book, Collective Intelligence which gave the idea that if we build an efficient program on a large set of data, then we can start observing interesting insights from it. And this led me to spend most of my time, playing and churning with the Data.

Now I understand that tools and techniques like Machine and Deep Learning are only helpful for about 10% of the data unless the domain is well understood. We must ask the right question to the data and the data confesses on its own. This can only happen when we are in the FAMILIAR domain with a purposeful approach and the right questions are put up. So that’s how my thinking and professional transformation has taken place.

Please throw some light on ‘Finding a Purpose’ and ‘Go to the why part before going to the How part’.

• In our profession Analytical thinking is an integral part of our daily activities. Whatever the problem statement only if have a keen interest in the domain we can grow into a Problem Stakeholder. And thus, finding a purpose within the problem is a must. Then only we can ask the right questions and exercise in the right direction. This is one of the triggering points that drives us into our profession.
• For example, I observed an organic interest fly within my team as were working on an analytical problem related to the COVID data set. I hope the starters realise the importance of finding the purpose in their work. This not only improves the overall growth and performance but also has a positive impact on work ethics.

While hiring someone in your team what are the qualities that you are looking for?

We as a team do not believe in the buzzwords and their occupancy in one’s resume.

• Honestly, if a technology is launched and within a span of two weeks or a month you have it on your resume, I am not a big fan of that. Because I don’t find this sustainable in the long run. Yes, an incremental learning mind is what we are always seeking. Being open to feedback and not taking offence to constructive criticism are some qualities that can help you grow in the long run.

With the right mindset, I believe anyone can be groomed with the right skills.

The professionals and the starters both want to know, where to start and how to keep up with new technologies emerging daily.

I will reiterate that fundamentals are your best friend.

• Even as professionals if we want to learn a newly emerged technology, the fundaments play an important role in adapting and exploiting the same. So do not worry about the buzzwords and focus on building a strong base for the techniques.

Please share your valuable feedback on Setu’s PGD course on Data Science.

• I got to know about SETU's PGD in Data Science course, and I will describe it best as a technique course and not a technology course. Using real-life data sets from industry experts is a commendable approach and will boost the confidence of the people undergoing this course to a great level. This helps them tackle the problem with the right approach and understand the realistic accuracy levels we target in the industry.

This initiative is a great step in helping the students as well as the professionals transform their careers in the right direction.

Keeping in mind all the groups from freshers to the people with decades of experience who want to learn Analytics and Data Driven decision-making, what suggestion will you leave us with?

1. I will say always focus on the job description and then choose wisely. Do not rely on the market terms and Titles as they are misleading. Understand the work and invest your time and efforts in the areas that interest you the most.
2. Always have an incremental learning approach as that is the need of the hour and it will keep you in the race.
3. The last piece of advice from my end will be to have a step-by-step approach so that you are not lost in this haystack of technologies, techniques and market gimmicks. Undertake and master the skills one by one. This is very simple and effective at the same time.

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If you are aspiring to Learn Data Science by solving Real Industry Data projects, please share your interest here. At SETU we have a unique way of training you. We are committed to developing Industry-ready Data Talents and helping you make the right Job Transition in this domain.