At INSAID, we create accomplished and empowered Data Leaders. We groom our students to dominate the world of Data Science and AI and reshape their future. We value what our students bring to the table. We share their vision and support them during their journey and ensure that they carve a niche for themselves.
We’re proud to have tutored exceptional students all across India. Today, one such exceptional student, Sathish Kumar Venugopal stands in the spotlight.
Student Name: Sathish Kumar Venugopal
Current Organization: Amber Road
Batch: GCD – August 2019
Total years of experience: 20 years
Malvika: Hi Sathish, before we begin, could you tell us more about your current work profile and your career trajectory so far?
Sathish: I have around 20 years of experience. So I initially worked as a Developer and then I moved my career into testing. I have spent almost 18 years in testing only; I started as a Test Engineer and moved all the way to a QA Director.
Before this, I was a part of Infosys. I was working as a Senior Product Manager at Infosys. After that, I just moved into Amber Road and for 4.5 years I worked as a QA Director there.
Malvika: What got you interested in Data Science & Machine Learning?
Sathish: So when I was leading the QA team, I was supposed to implement automation for all the 15 product lines.
In 3 years, I improved to 70-75% of coverage through automation.
In another 3-4 months, I planned that coverage could be increased to 80-90%. At that time, I started exploring things. I was learning about Machine Learning and Artificial Intelligence which was interesting and I started exploring more on Machine Learning algorithms.
I had the mindset to start exploring all I learned by implementing it in testing. So what improvements I can bring to testing through AI was my focus.
Malvika: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at INSAID so far?
Sathish: I have good exposure to Python. I have learned NumPy, Pandas, Scikit Learn, and Seaborn.
Along with that, I have a good grasp over algorithms like Linear Regression,
Logistic Regression, Random Forest and Decision Tree.
Malvika: Have you undertaken any projects to implement these tools that you’ve learned?
Sathish: I initially took up the EDA Project as shared by INSAID.
They have assessed one project. So I hope than that, and I have submitted that I have taken that Olympics data set, and then like tried to implement, which was a good one.
Malvika: What are some of the initial challenges you faced when you got started on your Data Science journey and how did you overcome it?
Sathish: It’s been a long time for me coding like almost 18-19 years. I have not been coding once I moved into testing. I didn’t do any hands-on coding at least for the last year.
Even for automation, we used to do some basic coding, not like full-fledged coding. Initially, I was feeling a little bit challenged when I was learning Python.
Basically, I’m from a Computer Science background so it was not difficult for me. I didn’t spend time all these years because I didn’t want to do coding.
Now when I started learning Python, it was very interesting. And I was I was happy to see I was able to do coding, and I was able to execute and get some results. I was also able to do the project. Python is a good language and it is easy to learn.
Malvika: What is the goal of Data Science? In your view, how has Data Science evolved in the last few years?
Sathish: Since I’m in the management role, what I feel is Data Science should be helping in understanding the business problem and then try to give some solutions using the Data Science and AI combination.
We should try to find a lot of business solutions. The main goal is to get the solution for the business based on the data that is available. That is the primary problem that Data Science is here to solve.
Malvika: What are the current trends in Data Science that you are most excited about?
Sathish: I have worked in different domains.
I’d be excited to see developments in the e-commerce and retail space because I have spent most of the time in e-commerce and retail. So I see already a lot of progress has been made in the e-commerce and retail domain.
If you look at Amazon, they’re doing great using recommendation engines to generate so much revenue. I think still there are a lot of opportunities in that area and a lot of new things will be coming to that area.
One more area, which I see is the healthcare space. I was watching Sundar Pichai’s interview in medical science where he shared that 90% of cancer detection can be done through AI.
All the fields are expanding, if we have domain knowledge in one particular field then all trends in that space will be super exciting. It will be more convenient for us to explore more things and help our company in business.
Malvika: Have you attended any of the speaker sessions that we have at INSAID?
Sathish: Yeah, I have not missed even one.
They were very useful and informative. I’m just moving into the Data Science space, so in real-time, how will things be is the kind of question that got answered during that speaker sessions.
Malvika: How has your journey with INSAID been so far? Do you have any comments on how the curriculum has been structured, the faculty and the support team?
Sathish: To be honest, I had no expectations when I joined because I was totally new to Data Science. So whatever the curriculum and whatever the course, it was good actually. Over time I realized the nuances, now I’m enjoying each and everything about this course.
It is structured in a very good way, and each and everything in industry sessions is very useful. Additionally, you are doing additional extra things like assignments, activities, projects, this is going to help us a long way.
Following proper guidance at INSAID, we can meet the goal of getting an opportunity in Data Science. I don’t know about others, but whatever you’re saying, I am strictly doing that.
Malvika: Who is your favorite faculty at INSAID and what did you learn from him the most?
Sathish: In my 3-4 months of journey, I had two faculties; Suchit and Lavi; both are good.
Suchit is excellent! Basically, for beginners who don’t know anything about Data Science, the way he explains is amazing.
At the same time, there is a balance between the different kinds of people there; experienced and inexperienced. Every student is wonderfully handled by Suchit.
He took classes in the initial two month period. Basically, the foundation is very much important. He made sure each and everybody understands the basics and he spent enough time explaining things over and over to everybody.
Lavi is also an excellent coach and mentor. He is very patient in answering all questions and he has very good, hands-on knowledge about the subject, and in-depth knowledge about the industry also.
Malvika: Crafting a great Data Science resume is a critical part of getting shortlisted for Data Science roles. Tell us some ways in which you have improved your resume as part of the Data Science Career Launchpad.
Sathish: Yeah, so this was one more thing I was surprised by; I know how to prepare my resume, but people who are new, need such sessions.
INSAID is putting in additional efforts and ensuring that each and everybody’s resume is industry-ready.
What keywords should go in? What are the pointers that have to be there? All the additional efforts you’re putting in for the students, I’m really appreciative of all of it.
It will help students looking for jobs, also for recruiters. It will be easy for corporates and for the candidates as well.
Malvika: INSAID’s mission is to Groom Data Leaders of tomorrow. What do you understand by a Data Leader? And how is a Data Leader different from a Data Scientist?
Sathish: Data Science Leader means he has to lead with example.
He should be an expert in the subject, simply knowing the concept does not make you a Leader.
You should be hands-on and you should be helping others, grooming others and guiding people in terms of which direction and where the industry is going. So first, that person has to know about all the future trends in his domain.
As a Leader, you will be leading Junior Data Scientists, Data Analysts or Business Analysts, all those people you should be able to guide and you should quickly be able to understand the business problem, visualize the problem and then you should have some initial solutions or suggestions.
Malvika: What is your advice to anyone wanting to start a career in Data Science?
Sathish: I can categorize Data Science students in two ways. You should pursue this field only if you fall into one of these two categories.
One, people who already have experience and feel like they’re doing a routine job and want a change. So Data Science will be a good opportunity for them because that is the upcoming technology.
Another category is someone wanting to explore new things, do something different every day. For those kind of people, Data Science and AI will be a good opportunity.
Malvika: Thank you for your time, Sathish. All the best for your future!