MyStory: How I became a Data Science Hacker from being a Delivery Head
It was a hot Sunday afternoon in June 2014. I still remember that day and recalling that day still gives me goosebumps.
I was browsing the internet looking for some interesting articles on Data Management, when a website called “Coursera” caught my attention. They were publicizing free online courses delivered over the internet.
I had never heard of them before and was not sure what to expect from these free courses. Eventually, I decided to explore the course material. That one click literally changed my life.
In this article, I am sharing my story with you, how I stepped out of my comfort zone and pushed myself from a successful Delivery Head into data science & machine learning.
My Career (From 1996 till that Sunday afternoon in June 2014)
First, let me take you through my career history. After graduating from Indian Institute of Technology, Madras (B.Tech in 1994, M.Tech in 1995), I started my IT career developing ERP software. After working for 3 years, I got a chance to pursue an MBA from Indian Institute of Management, Calcutta which I completed in 2000. This is when my tryst with Data Warehousing & Business Intelligence began, first with a consulting company and then with large IT service firms leading me to the position of Assistant Vice President handling a portfolio of 40+ million dollars.
The path that lay before me was also fairly clear – handle more accounts, larger teams, higher revenue targets. This could easily lead my way to the so called ‘top management’ in this IT services business.
But deep down, I was not happy. I was rapidly moving away from being a technologist, a subject matter expert into an excel junkie only worried about revenue, cost, attrition, recruitments & so on.
Not that these problems are trivial or un-interesting, it was just that I did not want to spend the rest of my career doing that work.
The Click that Changed My World
Back to that Sunday afternoon. Once I got into Coursera, it felt like a kid in a candy store. There were wonderful courses being taught by great professors from dream universities and to top it all – they were all free!
Very soon, I registered for the introductory “Machine Learning” course taught by Andrew Ng and was soon doing 3 to 4 courses in parallel. I had some background in Statistics but what was being taught as Machine Learning was really fascinating. By mid-2015, I had completed 12 courses in Machine Learning & Data Science across Coursera & edX.
Andrew Ng’s course was followed by 9 courses in Data Science Specialization from Johns Hopkins, Bill Howe’s Data Science course, Analytics Edge on edX and I was becoming increasingly confident in connecting the dots among various data science and machine learning topics.
Crossing the Chasm – From Conceptual Knowledge to Working Code
By June 2015, with the help of MOOCs and by sacrificing my weekends, I was able to relate to data science and machine learning concepts. But the bigger challenge I was facing, I was still not very comfortable writing end to end programs.
To overcome this challenge, I started looking for resources that could help. And then I discovered sites like Analytics Vidhya & Machine Learning Mastery which were focused on helping programmers write Machine Learning code.
Towards the end of 2015, I was able to write programs in R and started participating in competitions on Analytics Vidhya, Kaggle, Driven Data etc.
Though I was not able to make it to the top percentiles in these competitions, I was very happy working through the datasets and making my submissions. An additional advantage of participating in these Hackathons was interacting with top data scientists in these forums. I thoroughly enjoyed it and to improve further I started going through the approach & codes of experts.
Tale of Two Lives
In early 2016, I was still in my day job that required handling teams working on Data Management & Business Intelligence projects for Banking & Financial Services customers. While I was utilizing late nights & weekends to work on Machine Learning.
It was becoming unviable to lead two different lives and by mid-2016, I decided to join a start-up focused on Analytics, Data Science & Machine Learning.
I feel that I have finally found my calling in life. By working on use cases for large Fortune 500 organizations, I am beginning to see the power of analytics in action. I only wish I was 10-15 years younger but as they say “better late than never”.
My Future Plans
I believe that we are at the cusp of a huge wave of business solutions powered by data & data science related techniques. I want to utilize my experience to formulate appropriate use cases, the solutions to which could help organizations provide better products & services. Also, India with its young workforce can become an analytics superpower by nurturing high-profile, talented data scientists. I would like to contribute by way of providing training & mentoring interested people.
What motivates me to keep going?
My motivation stems from the fact that in a future going to be driven largely by technology, data science could be our answer to provide a better, healthy world for coming generations. In general, I am a big fan of the Open Source movement. The fact that many talented people spend their priceless hours to create fantastic software to be made available for free is a big inspiration for me to give back something to society.
My learnings – Distilled into the World’s Largest Analytics Mind Map
I have spent a considerable portion of my career working on all aspects of Data Management & Business Intelligence. Those concepts along with my recently acquired (2.5 years) data science knowledge puts me in a unique position to appreciate all aspects of data-driven decision making geared towards delivering business value.
I have encapsulated this knowledge in a mindmap, which I claim to be the world’s largest analytics mindmap (1800+ nodes) accessible at this link: https://bit.ly/31KArT8. My goal is to make this mindmap as an anchor point for all Data Science practitioners to understand the broad canvas of analytics and appreciate this wonderful field in a holistic manner.
Advice for beginners in data science
These are very exciting times for people entering the analytics & data science industry. There are tons of opportunities to make a name for oneself. Having said that, the basics are not to be forgotten –Develop business understanding, Be curious about technology, learn programming and more importantly, never give up!
About The Author
Karthikeyan Sankaran is currently a Director at LatentView Analytics which provides solutions at the intersection of Business, Technology & Math to business problems across a wide range of industries. Karthik has close to two decades of experience in the Information Technology industry having worked in multiple roles across the space of Data Management, Business Intelligence & Analytics.
This story was received as part of “What’s Your Story?” contest on Analytics Vidhya. We found his story inspiring and hope that it inspires more and more people to this fascinating world of Analytics and Data Science.
Disclaimer: Our stories are published as narrated by the community members. They do not represent Analytics Vidhya’s view on any product / services / curriculum.