Meet Gopi Krishna Rajasekaran From Symantec

Working with analytics daily, digital marketer and search specialist Gopi Krishna Rajasekaran realized that data is what will drive industries and companies in the near future including online marketing. As more companies take refuge in the digital landscape, he thought it was high time to study data science and enrolled for the Certificate in Data Science Foundation (CDF) program at INSAID. 

In this interview, lets see what he has to say about the interception of data science in the online marketing domain and how his experience has been at INSAID. 

Question 1: Which program & batch are you part of at INSAID & tell us more about your current work profile?

Gopi: I am part of the Certificate in Data Science Foundation (CDF) program, July 2020 batch. I am currently working in Symantec, the makers of Norton Antivirus and hold the position of Search Specialist. My responsibilities include search marketing which in other terms is also known as online marketing. I run data driven campaigns. So, my work is purely data based. I take every decision based on data and don’t rely on guesses or generic estimations.     

Question 2: Walk us through your career journey & what got you interested in Data Science & Machine Learning?

Gopi: I started my career back in 2008-09 as a conventional marketer. I did my MBA in marketing and systems, started working as a marketing executive. But after a year, I thought the role wasn’t perfect for me and wanted to do something different.  At that time I was very passionate about the internet as is now. During that time ecommerce was relatively new. So I tried my hands in online marketing and search engine optimization. 

And then with each passing year, as technology developed more, several things came to the forefront. There were social media ads and paid ads, etc. There were a lot of tools to run campaigns and we also had analytics tools to measure return on investment on those campaigns. And, that’s when I started having real fun doing analytics. 

Through analytics I found my love for data. Right now, every business owner wants to know what they get out of their investments. So when any business runs an ad, they would obviously want to know the number of conversions from the ad, they want to measure everything. And that’s why we need data. 

Data offers us the opportunity to measure and scale outputs. Through data we can predict what will work and what won’t. And I think that’s something which attracted me towards data. And as I am pretty good in web analytics I can say that data, nowadays, doesn’t only come from websites. It can come from anywhere, may it be ads, apps, online books and others. 

And, after COVID-19, almost all businesses are turning towards online platforms. So, online platforms along with data science are the future. DS and ML have extensive scope in business and they are actually impacting the digital marketing landscape. 

Companies like Google have already started applying machine learning algorithms on several analytics tools that only eases a lot of the work but ensures online security from data thefts. 

So, being a digital marketing specialist, I should also study data science and equip myself with concepts like data science and machine learning. And tomorrow, who knows I might be in a position to collect millions and billions of data from a campaign and create a model out of it.  

Question 3: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at INSAID so far?

Gopi: After I started to study data science, I have mastered Jupyter Notebook, which is the integrated development environment for Python. And it’s really cool. All these days I was using PyCharm, which was big and complicated. But Jupyter Notebook is really light. Especially when it comes to commenting on things. 

Apart from that I have also mastered packages like NumPy, Pandas and Matplotlib in data science. Right now, I’m eagerly waiting for the machine learning module to get started by the faculty. And I’m really excited to learn about new packages in it.

Question 4: What were some of the initial challenges when you got started on your Data Science journey and how did you overcome it?

Gopi: Initially, I had some challenges when I started to study data science and it was allotting time for revising the data science lessons. But then I overcame it by allotting my early mornings for revising my lessons and then proceeded with daily work. This allowed me to balance both of them. 

Starting to study data science, I also had some challenges in handling Python based tools like Jupyter Notebook, installing packages and understanding them, and some of the data science concepts as well. 

But, because I know it’s very difficult for the faculty to cover all topics within two hours of class, I looked them up on Google and understood it by myself. I generally follow a self-learning concept so that whenever I am in doubt, I google it to find the solution.

Question 5: What is the goal of Data Science?

Gopi: The goal of data science is to extract business focused insight from the data. It can be real time data, or it can be historical data, or data based on future predictions. When you study data science, you make the decision of how to run a business based on your past, present, and future prediction. 

And I think for this, we need to have a clear understanding how the data flows, and what’s the value of that data. And I think we should also have a very powerful and skilled workforce who knows all the concepts of data science and how to handle data in a proper way. 

And in case of what the goal of data science is in my career, I would say that I wanted to combine data science and digital marketing to optimize analytics, especially, for the e-commerce sector. 

And I believe, if I study data science, it will help me in the long run so that I can become a better data analyst or data scientist; or at least it’ll help me to get a hang of data and will help me to make better data driven decisions.

Question 6: In your view, how has Data Science evolved in the last few years?

Gopi: I think in the last few years, data science has evolved tremendously. Right now, we have more data than we have oxygen on the face of this planet. With the help of real time analytics, lots of businesses have started generating real time data as well and use them to make instant business decisions. 

Data scientists, too, play a very important role when it comes to real time data as by using real time data they help businesses build ML models to optimize processes and profitability. 

One of the best examples of this would be undoubtedly taxi apps like Uber and Ola. Just imagine, like four to five years back, nobody thought that we would need a mobile phone to book taxi cabs. But now we can’t even imagine calling a cab without our mobile phones. That’s the power of data science, ML and AI.  

Question 7: What are the current trends in Data Science that you are most excited about?

Gopi: The current trends in data science, which I am very excited about is the advancement of transportation apps like Ola and Uber, the use of data science and machine learning concepts in the insurance industry and by Apple. 

Transportation apps like Uber and Ola are doing a wonderful job in understanding user behavior. Based on historical and behavioral data of customers they understand just what the customer needs and provide that through their services automatically increasing the apps use. 

I have also come across one specific site in which I read that insurance companies have already started using data science and machine learning concepts. Based on the customer’s existing data or health status, they predict the future condition of their health. And it is based on these findings that they recommend insurance plans. 

Apart from that I am also excited about the machine learning and data science concepts used by Apple. They come up with new devices and models each year. 

One prominent example of data science and AI applications in Apple is the Apple Watch that can detect early signs of cardiac arrest and alert the user so that they can then take necessary precaution.

Question 8: Which are some of the blogs that you follow?

Gopi: I follow data science pages from Reddit and Google News. I also read blogs from Data Science Central, KDnuggets, Kaggle, and Revolution Analytics.  

This was a conversation with one of our CDF students – Gopi Krishna Rajasekaran. 

For more such interesting student interviews, go to INSAID Spotlight.  

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