Your DS Story S01E08: Roshan T John (Awok.com)
‘Your DS Story’ is my attempt to bridge the gap between data science professionals & data science aspirants. Here new crop of data scientists will share their experiences, struggles, achievements & their advice so that data science aspirants/enthusiasts can learn and get inspired.
Roshan T John is an experienced Data Scientist with 7 years of experience in multiple domains. He helps companies make sense of Data and make subsequent Analytical and Machine Learning models.
1. Please tell us a bit about your background?
I grew up in Abu Dhabi, United Arab Emirates. After high school, I moved to India to pursue my Bachelor’s degree at the National Institute of Technology, Trichy.
By the final semester, upon consultation with my college Alumni, I was knew I had to pursue a career in Research and Predictive Analytics. However, back in 2009, Machine Learning wasn’t very popular and most of the times unheard of. So most of the jobs offered by my placement cell weren’t having this requirement in the job description. So I decided to do something unconventional; I chose to opt out of the college placements and started to search for jobs myself.
After networking for a while, I finally landed a job in the Indian Institute of Science which is like the MIT of India. Due to lack of budget for the projects, I decided to work on a voluntary basis for the first year as I was more passionate about my project than the pay. Ever since then it has been an amazing journey, as I had the privilege to work for a wide variety of companies, MNCs like GE, Robert Bosch, Academia like IISc and some startups.
At present, I am working as a Data Scientist at Awok.com. It is a Dubai based e-commerce company that has one of the highest online users in the country.
The beauty of Data Science is the massive amount of knowledge it has to offer and hence learning never stops. I am not sure if there is a Data Scientist out there who knows everything. There is always something new to learn. You could always go in depth such as learning the new algorithms, new scripting language or in width such as learning Cloud Computing, Big Data etc.
2. What projects you are working these days?
Currently, I am leading a team to build an on-the-fly Recommendation Engine from the ground up. I’m really excited about this project and I feel privileged because only very few Data Scientists get to work on building a Recommendation Engine from scratch. This Engine will help the company in increasing the user session time and overall revenue of the company.
3. How your day to day job looks like?
A typical week looks like coding on multiple IDEs, guiding fellow Data Scientists, coordinating with other Data Science Professionals, setting up side/future projects with various Business Stake Owners.
Apart from this, I also collaborate on GitHub projects, learn something new (MOOCs), mentor Data Science aspirants, attend meetups and participate in Hackathons.
4. How you started with DS or transitioned into DS?
Since the beginning of my career, I have been involved in Hardware Machine Learning projects, some of them being IOT devices. This is a tad different from Software Machine Learning projects as the dimensionality is very low, though the data was huge. Besides, these were all Waterfall projects and the models could fit and be visualized within Excel itself.
I was sure that to have a faster learning curve, I had to shift to Agile projects. So I took up a course from Zenrays Institute to brush up my knowledge on Statistics and learned the advanced algorithms such as NLP and Computer Vision. This helped me in transitioning my career by securing jobs that focused on Agile Machine Learning Projects.
5. What advice would you like to give to DS starters or DS transitioners?
I have actually written an article on this, i.e the skills required to be a Data Scientist and how to improvise. In short, Math, Coding and Communication.
Remember to avoid “Positive Procrastination”. This is when a person thinks “I will only start/transition to the DS career when I have learned everything”. This is close to impossible. As mentioned earlier, as this field is moving at a fast pace with almost a new innovation every week. I would recommend learning the basics that are required to get your first job and when you are on the job go deeper into the fundamentals.
Brand yourself. Start at giving back to the community by forking from Github/ Kaggle repositories. Linkedin is a powerful tool and also the most underrated. Begin posting the latest innovations in Data Science and getting engaged to other related posts.
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