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, Venkata Narayanan Mohan stands in the spotlight.
Student Name: Venkata Narayanan Mohan
Current Organization: Indian Bank
Batch: GCD – April 2019
Total years of experience: 10 years
Malvika: Hi Venkata, before we begin, could you tell us more about your current work profile?
Venkata: I graduated in 2009 from my engineering. I joined the Accenture as a Software Developer. I was basically an IT core professional for 5 years and then I joined a public sector bank. I’m a Manager at the Indian bank and I started here 5 years ago.
Malvika: What got you interested in Data Science & Machine Learning?
Venkata: For the past 2 years at Indian Bank, I’ve been handling a lot of data for core banking solutions. data we are handling.
We are looking for patterns in our collected data but I was mainly just collecting data on Excel and reporting to the senior management.
When I started the analysis part in Excel itself, I was able to relate to data. That’s how I started looking into Data Science.
Malvika: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at INSAID so far?
Venkata: For the past 8-9 months, I’ve been working with Pandas, Scikit Learn and Numpy. These packages I’m comfortable with.
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?
Venkata: I struggled mainly with allotment of time to this new line of study/career.
Since I was from a technical background, coding was not a problem. Time management was a hassle. Then I started following INSAID’s recommendations on the same. They said to spend around 30 minutes daily on this and I followed that up to 3 months and then I was able to develop a pattern/schedule and was able to manage time more efficiently.
Malvika: What is the goal of Data Science? In your view, how has Data Science evolved in the last few years?
Venkata: Actually, the primary objective of Data Science is we use data to find some insights.
It’s not an Excel-based analysis, it requires domain knowledge also if you’re working as a Data Scientist. So data is mainly used for deriving some insight, giving some action items out of a confusing data set. It seems like from nothing, we create something, some actionable items so that you can act upon it.
Malvika: What are the current trends in Data Science that you are most excited about?
Venkata: From the beginning, I relate everything I learned, every single class and every single concept to my domain. Whatever project I’ve done so far is also from my domain-banking.
The main trends I am excited about are Fraud Prevention and Marketing Strategies like segmentation.
Building strategies to target the right section of prospects is applicable across industries and very valuable to businesses alike.
The second trend would be fraud prevention and predictive analytics in our domain.
Malvika: Which are some of the blogs that you read? Which are the top two Data Science & AI influencers you follow?
Venkata: I always scour the internet for current trends in banking & AI and banking & Data Science and banking & Machine Learning.
We all use Medium, we use towardsdatascience, Analytics India Magazine, also does great work when it comes to relaying quality information.
Also, I visit some particular company websites like Citibank and Wells Fargo. Whenever I see some news on these financial services domain websites I go dig up on that and then see what they’re doing with it.
Malvika: At INSAID, students are encouraged to build high-quality GitHub profiles. Have you built a GitHub portfolio and how do you think this will help you?
Venkata: Everyone these days is referring to GitHub because it provides a nice platform to display all the codes, presentations, videos, and all your previous work that you can upload.
The sessions were helpful in helping us build the optimum profile.
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 Data Science Career Launchpad.
Venkata: Of all the sessions in the Career Launchpad, I found the resume session the most useful. After attending that session, I formed the master resume they told about in that session, and then according to the job description, I was drafting separate resumes and cover letters as well. So that was a great experience.
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?
Venkata: A Data Leader is a person who takes the first step and goes out of the box out to lead other Data Scientists.
While Data Scientists are running in one direction to find accurate solutions, Data Leaders put in some extra efforts to improve either the ability of the Machine Learning models or data insights whatever it takes to lead other Data Scientists.
Malvika: Who is your favorite faculty at INSAID and what did you learn from him the most?
Venkata: There will be two faculty I’d like to name. Deepesh and Suchit are amazing.
i can’t choose between these two faculty. Deepesh has been very helpful, he has been the Machine Learning Trainer and so my Machine Learning concepts were very solidified.
I’ve been following Data Science for the past one year even before I started the course. I was learning from YouTube, I was learning all these Machine Learning concepts.
But because of Deepesh’s teaching, I made the first ML model.
Malvika: What is your advice to anyone wanting to start a career in Data Science?
Venkata: I don’t have much experience to suggest much. I will talk abou how significant execution is.
It is very critical that we execute what we learn. Hard core efforts in programming and execution is very important. Also, they should align their domain and their learning together.
Malvika: Thank you for your time, Venkata. All the best for your future!
