Vijay Pravin Maharajan is a TEDx Speaker and a Data Analytics Expert at Siemens AG.
He has recently been featured as of one of the AI Time Journal data scientists to follow in 2020.
We thank Vijay for sharing how he got into data science and touching on several key aspects of being a data scientist, including the importance of technical skills, domain knowledge, and a continuous learning mindset.
This is interview is part of the Data Science Interview Series 2020.
How did you first get into data science?
I did my Bachelors in India in Electrical Engineering. After doing my Bachelors I came to Germany to do my Masters. I did Masters in Electrical Engineering from one of the top universities in Germany – Technical University of Munich (TUM). During my second semester, I got an opportunity to work with Telefonica GmbH as a Working student. I was asked to support a data science project 2 months into the work life. I was so fascinated by what I did on that project. Then I started taking up optional courses at university, and in the mean time, I started learning Python. Few months later, I got an Internship on a data science topic. Then I did my Master Thesis as well. Since I did my Master thesis really well and secured top grades from the professors, I landed up as a Junior Data Scientist at Telefonica.
How is data science used to create value in your current projects?
Data Science brings more valuable insights from the data. It helps to find the hidden patterns within the data. It also helps in crucial business decisions. In a nutshell, it helps businesses grow on an exponential curve.
What are the key skills that you use every day as a data scientist, and how did you develop them?
A good Data Scientist should have a really good mathematics skills, especially Statistics basics right. Analytical skills are important as well along with logical thinking. Coming to the programming part, either Python or R language is sufficient. But one can’t be a Data Scientist overnight. It takes days, weeks and months to master the art. Even after so many years of experience, it still feels like something fresh, for every new project. It’s always a learning curve when it comes to data science.
What are the top challenges you currently face as a professional data scientist, and how do you go about tackling them?
Data Quality is always a stuff to ponder about for every Data Scientist. Most of the data scientists spend a lot of time in cleaning and refactoring the data. And then, the gap between the data world and the business world. Sometimes, data guys doesn’t get the business values, and the business people can’t fully understand the technical solutions. Becoming a decision scientist, rather than a data scientist helps. Proper communication skills and analytical thinking gives a bit of edge.
How important is the domain knowledge of the business/industry you’re in as a data scientist, and how did you acquire it?
In my perspective, domain knowledge helps leveraging the technical gap. Over a period of time, one needs to understand the business well enough. Taking up workshops, or plant visits (if it is a production company) helps!
Do you create data science content?
I write snippets, blogs and articles on my LinkedIn page where close to 25,000 Professionals follow me.
3 words that best summarize how you learned ML and data science:
Practise. Patience. Persistence
People: who are some inspiring data scientists and people in AI that you follow?
Andriy Burkov, Sudalai Rajkumar, Michael Taylor
Conferences: which data-science-related conferences that you attended have you particularly enjoyed and why?
I was Invited as a Guest Speaker in an International Conference on Big Data Strategy Dialog, at Bonn, Germany in May, 2019
And I was also Invited as a Guest Speaker in an International Conference on Big Data Analytics, at Frankfurt, Germany in June, 2019
I enjoyed both these conferences, as I got an opportunity to speak with experienced data professionals from Germany. And the panel discussions with the attendees were handy.
And then got a chance to present in front of my home crowd. I was invited as a Guest Speaker in the Machine Learning Developers Summit, at Hyderabad, India in January 2020.
What are the top 3 resources that you use to keep up with the advancements in the field?
Blogs, LinkedIn groups, Twitter feed
What is the biggest improvement that you introduced in the last 12 months that has considerably improved your workflow?
The Mindset! The mindset to learn one after the other, and the willingness to learn. Be it from a junior or a senior, I never fail to learn. And I will continue this amazing learning curve.
What advise would you give to someone who wants to get into data science today?
No matter what your background is, be confident. Be patient and keep learning new stuffs every single day! This Data Science Journey will amaze you, if you do it right and if you do it consistently.
Your favorite thing about working in data science:
Data Visualization
What inspires you about working in Data Science?
The changes I could see on so many data products around me in my day to day life
