Data Science is the next big transformational wave hitting the IT sector. And unlike many other sectors, it is a field dominated by a steep learning curve where you may or may not need a formal education or advanced degree, depending on your educational background.
Now, data science that evolved from advanced statistical analysis existed as a function for more than a decade, yet the lack of formal education environment has prompted many aspiring Data Scientists and Analysts to chalk a new learning path by brushing up on the programming, statistics or Data Structures to develop a thorough fundamental understanding and deliver outcome-oriented results on the back of data.
Given this backdrop, every week, we reach out to the community and speak to Data Scientists/Data Analysts and dig into their learning journey and what they like most about this buzzing field.
This time, we caught up with Sudharsan Ravichandiran, Data Scientist at Param.ai, to understand how he was drawn to this field, his big leap, what he likes most about the job and how he strikes a work-life balance.
Interestingly, Ravichandiran, author of Hands-on Reinforcement Learning With Python and Hands-on Meta Learning with Python started off as a freelance web designer during his undergraduate studies and even designed some award-winning websites. “I had this paper called Artificial intelligence on one of my spring semesters which drew my interest and got me fascinating. That’s where I started to explore more about AI. Being a huge Math enthusiast, after discovering substantial math behind ML algorithms, I decided this is what I should be on working on,” he said.
At this thriving startup, everyday comes in with new challenges which keeps him excited and motivated to make him want to go to work every day.
Life at Param.ai
Talking about his day-to-day role at Param.ai, an AI-powered intelligent recruiting platform, Ravichandiran shares that the platform maps potential candidates to corresponding jobs and ranks them in order of relevance. “Being a Data Scientist at Param.ai is exciting as every day brings exciting challenges and opportunities to grow,” he said.
Everyday is not the same for Ravichandiran. Some days, he is hard at work building actionable latent insights derived from huge data points while some days he’s involved in working on building models. However, most of the time is spent on getting, cleaning, standardising and understanding the data.
“If you understood the data built then all other steps come very handily. On the other hand, but if you don’t understand about the dataset which you have then there is no use of applying algorithms,” he shares.
Ravichandiran’s recent project included building a powerful recommendation engine that continually learns the behaviour of recruiter to understand their hiring traits which include numerous parameters such as candidates the recruiter is shortlisting and hiring for the respective job role. The recommendation system is robust enough and since it learns continually, if the behaviour/activity of the recruiter changes, the model also updates itself and learn from there.
Striking a work-life balance
Work-life balance at this startup is simply amazing and he reveals he gets constant support and guidance from his amazing managers Hari and Ashish. Meanwhile, outside the job, he loves working on creative stuff. Ravichandiran is good at songwriting and sketching and also a big fan of pop music. “If you don’t find me playing with data then you can probably find me either playing songs on my dashing guitar or listening to pop music,” he shared.
His advice to beginners
His suggestion to someone getting started in data science is to ensure they understand the fundamentals. Before jumping directly into modern algorithms, he suggests them to build a strong foundation on basic and also Math including linear algebra, probability statistics, and calculus. “I also recommend beginners to code algorithms from scratch instead of using high-level APIs. Coding algorithms directly from scratch will undoubtedly strengthen their understanding of the algorithms and take their skills to the next level,” he shared.
According to Ravichandiran, the spurt in interest can be cited to an exponential growth in AI over the last two years. “This is mainly due to the modern computational advancements and the availability of humongous volume of data. Today, many researchers and scientists around the world are working towards Artificial General intelligence where machines can perform multiple intellectual tasks just like we humans do,” he said, in closing.
