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Member spotlight: Neeraj Jangid, Southern Methodist University

By Christina Howell posted Thu December 12, 2019 03:06 PM


Spotlight Interview: Neeraj Jangid

Masters Engineering Management Candidate at SMU and Data Science Blogger

Featured members such as Neeraj come to us by way of our community spotlight nomination program. Do you or does someone you know have an interesting data science story to tell? Nominate them here!

Neeraj Jangid is a budding data scientist who is currently enrolled in a masters in engineering management program at Southern Methodist University. After being introduced to data science at school, he decided to start blogging and sharing his knowledge and enthusiasm with other prospective data scientists. He has contributed a
series of blog posts and discussions on the IBM Data Science Community and also blogs at The Datum. We spoke with him to learn about his passion for data science and his career ambitions. (This transcript has been edited for brevity and clarity.)

Q: How were you introduced to data science? 

A: I was first introduced to data science when I started my masters in engineering management in Fall 2018. I had two courses in data science. I had heard of it, but never had the practical or personal experience on how things work. They were using R for data analytics and Tableau for visualizations. I was fascinated and decided to do my major in data science while pursuing my engineering management degree. 

Q: What was the deciding factor in making data science your major?

A: It was a good fit for me because most were getting into IT, C programming, python programming, javascript. I didn't understand that so well, but when I was exposed to R - it is a more intuitive language. A straightforward statistical program - with just a few lines of code you get an output. I was never a coder, but I understood it well. And Tableau was more interesting because you could plot different graphs and get insights from what they are trying to tell us and try to convey it to people. We are more visual than verbal - we understand things and remember it better if we see something. If given a graph you could better understand millions of rows of data, how they behave, where things are not working, and where to correct them. 

Q: What is your dream job?

A: Pursuing a job as a business analyst for major companies. How are you going to roll out the product, how many people are you going to test, what are the KPIs to evaluate your project, if something is wrong then how much more data would you need to test? Do analyses to make the product better.

Q: How did you first get involved with the IBM Data Science Community? 

A: When I started blogging, a friend suggested I join a few data science communities where I could see how things are going and what people look for. I was interested in writing simple blog posts where people like me who were never exposed to data science but might be interested. I had no prior experience blogging. I just did a web search for best data science communities and IBM's was one of them. I joined for that reason. When I started posting, it also gave me a lot of views on my own blog in return -- 20 to 30 percent of my traffic -- so I started posting more regularly. I would get personal comments and emails from IBM Data Science Community members with suggestions or changes or different views on what I posted. Say I posted something on visualization, people emailed me about different approaches for visualization. I would get good feedback from the IBM Data Science Community, and not from others. 

Q: What excites you about data science and machine learning?

A: It obviously has a big role to play in the coming couple of decades. I think that data is the most important thing today. You can do much more if you have the right data, and can do the right analytics on it, it tells you about how you can move forward with your product or your business to stay ahead of the competition or improve your functions or products. Broader concepts like AI also excite me.

Q: How do you stay on top of data science trends and practices?

A: If I want to learn a new concept, I first go on YouTube because I can learn faster than reading something. I might then search for a book that could help them. 

Q: What would make a Meetup attractive to you?

A: Giving a practical approach and insights into how things work in companies - how they use analytics and case studies showing how data science actually helped their products. So I can map to their expectations and prepare myself to improve my chances to work for those companies.

Q: Do you have any feedback on the Data Science Community?
A: I really benefitted more than expected from the IBM Data Science Community. It would be useful to have more practical data science case studies, so we users can get insights into how things are working practically. 


Q: What inspired you to start your own blog, The Datum?

A: I was interested in writing basic blog posts so that people who were never exposed to data science, like science is booming. Everyone knows the term, but not what it means, the understanding to give them a good base. I wrote 10 blog posts and got good responses. It was read in 79 countries, got about 100 views per day. I think I was able to do what I was expecting for myself. 

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