What do you need to become a Data Scientist?
- Srdjan Santic Interview

Danica Bozin, Serbia

Marketing Manager at Data Science Conference / 4.0,
Physics student

“Data scientists are kind of like the new Renaissance folks, because data science is inherently multidisciplinary.”
- John Foreman

Many of us are wondering how we can cross the big gap between our current position and landing a data science job. Last year at the Conference we had an opportunity to speak with data science experts about diverse topics, from education to current and future trends in the field. Luckily for everyone we documented most of the content we provided at the Conference! One thing that barely anyone had a chance to see were these incredible interviews! We’ll be sharing them every Thursday from now on, and each will explain a different part of the data science world.

Let’s begin!

All scientists are data scientists

The story of every expert must begin with their education, and that’s the topic we’ll share first! We spoke to Srđan Šantić, a data science mentor at an online learning website called Springboard. There were plenty of questions we got to ask him and you can watch the full interview here. But in this text I’d like to highlight just some of the most important points.

We started our conversation trying to pinpoint the skills a data scientist needs in order to join the workforce. A decent level of math and coding skills are a must, Srđan said, but what sets truly great data scientists apart is the ability to read into the data and tell its story. This means that humanities, to our surprise, play an important role in data science. In many projects and jobs you need to understand people to make meaningful connections when you analyze data, and when you are presenting your findings. The story you discover when working with numerous data sets is the story you must convey to people that understand far less than you do, and its where truly exceptional really shine.

Stay relevant in years to come!

Srdjan doesn’t think that there will be any shortage of jobs in data science anytime soon, so even if you are just starting out your career is future-proof! This is great news for all the enthusiastic minds that may have a different background such as Mathematics, Physics or Software Engineering, because aiding those skills with the ones you’re missing, from the above mentioned, is a surefire way of becoming eligible for data science jobs!

Additionally, even humanities majors may become data scientists today as we emphasized that certain skills in these fields are extremely important. Furthermore, Srdjan goes on about how Natural Language Processing (NLP) is becoming a new trend and almost “common knowledge” for all data scientist, which means that if you are a linguist interested in diving deeper into this research, learning some math and a bit of coding could land you a job in data science! NLP will lead to better chatbots our interviewee goes on to conclude.

There’s a lot more that we talked about, such as deep learning, self driving cars, data science trends and what are some major business struggles when it comes to products that use data as their driver. To hear Srđan speak about these topics don’t miss out on the full video interview (lasting about 5 minutes) and join us on youtube for more interesting content from last year’s conference.

Should you pursue Data Science?

“Nobody ever talks about motivation in learning. Data science is a broad and fuzzy field, which makes it hard to learn. Really hard. Without motivation, you’ll end up stopping halfway through and believing you can’t do it, when the fault isn’t with you―it’s with the teaching.

Take control of your learning by tailoring it to what you want to do, not the other way around.”

- Vik Paruchuri

To conclude, if you have enough motivation to start learning data science there’s no reason not to, considering the time we live in. There are plenty of resources out there (edX, Coursera, Springboard, etc.) that can help you on your journey, and many are free! We encourage you to try and maybe we’ll get to see you this year at Data Science Conference / 4.0

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