The popularity of data science is a secret to none! The scope and demand of the field has taken the world by storm, and for all the right reasons!
Today, data has become the way of life to keep up with competitions and come up with better services that appeal to the audience.
Previously Rohit Katariya, AVP of Data Science, Naukri.com shared his valuable insights about the behind-the-scenes of how data science works.
But how do you start off in this field? To give us an insider’s perspective into the life of a fresher pursuing data science, we have Ramprasad Balkrushna Rakhonde, Data Scientist at Naukri.com sharing his experience.
Let’s dive in!
Could you please tell us a little about what you do?
I work as a data scientist with Info Edge. The major focus of my work is on job searches on Naukri.com. We work to optimize the job search results so that the most relevant and best jobs are shown to the user from a vast job pool.
What got you interested in this field?
Since childhood, I have been interested in computer science and college provided me the opportunity to explore various fields in computer science.
When I came across data science and Machine Learning (ML), I was enchanted by their applications. This piqued my interest in learning more about machine learning and my curiosity led to learning more and more and culminated in my passion for ML.
Once you found your passion, what was your next step to make a career out of it?
After discovering my passion, I began to learn about ML from online sources, college courses and to get a first-hand experience tried my hands at developing some models.
During this time, I got to know about the various pan-India machine learning competitions organized by various firms.
So simultaneously along with my studies, I started participating in these competitions. I did an internship in Natural Language Processing to deepen my understanding of machine learning.
Which college did you graduate from? And do you feel your college prepared you for this job role?
I am an alumnus of IIT Madras (IITM).
IITM provided me with numerous opportunities to delve deeper into my passion. With many electives focused on data science and ML, the institute provided us with the best teachings.
IITM also has an Analytics group that focuses on the practical application of acquired knowledge. So, by providing us with all these facilities, IITM helped me on my journey.
How did you get your first break?
The national level ML and data science competitions are the most real-world experience you can get while in college.
I got a real boost when I became the National Finalist for Mavericks, an ML competition, and placed among the top 10 teams from all over India. This was a great learning experience.
As for my first professional break, I bagged my job as a Data scientist for Naukri.com, Info Edge through campus placement.
What are some of your key responsibilities as a Data scientist?
Info Edge’s data scientist team caters to pan India data related demands for Info Edge. I work with the Seeker Search team on naukri.com.
Some of the key responsibilities include;
• Delivering the most relevant and best jobs to users from large pool of jobs
• Creating a seamless and quick search experience for users for better user interaction
What has the learning process been so far?
I have completed 1 month with the data science team. The learning process has been incredible so far.
I was able to learn about the amazing work the data science team has done and various projects that are in progress.
My understanding of data science and practical applications has widened. I am looking forward to the steep learning curve that the data science team has to offer.
If not a Data scientist, what would have been your alternate career choice?
I am fascinated by data science and machine learning. If I had to choose an alternate career, I would like it to be in the machine learning domain.
I would like it if the career offered research as well as practical application opportunities like the current data science team.
Were there any specific skills you focused on developing to land this job?
It is important to have a thorough knowledge of the foundation of data science which comprises of a good in-depth understanding of the mathematics behind machine learning and statistics and probability concepts.
Apart from these, knowing the basic models thoroughly results in an easier understanding of more complex models.
How has your experience with Naukri been so far?
My experience here has been very pleasant. From the induction program to starting work on my first project, each stage has been well handled.
One of the best things is that all colleagues and mentors are friendly and approachable. This created a warm welcoming atmosphere at Info Edge, which allows a fresher to thrive.
How was your experience transitioning from a student to a working professional?
There is always excitement and a little anxiety when starting your first job. Now that I am familiar with the job, I’m more at ease.
As a student, you only have an idea and can’t see the real picture of industry at work.
After spending some time on the job, I can say that the transition from student to working professional is facilitated by the knowledge imparted by firms to students.
In my case, it was smooth sailing and exciting.
What were you expecting from this job? How different did it turn out?
As a student, I thought a data scientist’s job would be more focused on model building and deploying. More time would be required to optimize models.
But in reality, data engineering that is more important and requires a great deal of justified time. This job also came with an opportunity.
As a student, I worked with only a single model, but here, multiple models work simultaneously to achieve one great result. This has me excited and I am looking forward to working with the data science team.
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In this series, we aim to explore the career journey of people from different fields, backgrounds, and career stages who have tread the path and made a place for themselves in their specific areas.
Join us as we try to understand all about what they do, how they started, and where they are headed next.
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