Blog: Who is data science for?
Before the dawn of industrial revolution, if you had asked “Can anyone learn to read?” the answer would definitely be a big NO — books were pricey and reading books was considered a hobby of the elite class. But now, over the last few centuries, the majority of the global population has become literate. If you had asked a few years ago “Can anyone become a data scientist?” the majority of answers would, unfortunately, be no. Today, you ask, “Can anyone become a data scientist?”, the straightforward answer to this is definitely a big YES. With stereotypes around data scientists ( that they are all programming geeks and hold a Ph.D. in science or maths ) and many other misconceptions around what becoming a data scientist is like ( that they are disconnected from the real world and in front of their computer all night), the instinct might be to say no. However, it should be clear to us that human potential is infinite and we are only limited by our assumptions of what we are capable of and our access to effective learning resources.
What sort of person is suitable for a data scientist career?
Who is Data Science for?
There are a lot of similar questions we often get asked at Springboard from professionals when they consider learning data science. The easy answer to these questions is — “Data Science is for everyone- right from the millennial generation to generation Z. Everybody uses it, consumes it, and practices it to some extent.”
The team at Springboard had the privilege to talk to Jaidev Deshpande, Senior Data Scientist at Gramener and here’s what he had to say on “Who is Data Science for?”. This video is part of Springboard’s effort to help people understand what sort of person is suitable for a data scientist career.
Data Science is not just about your education level, qualifications, and skills but there are many more factors that you should be aware of when assessing your career potential as a data scientist. That’s not to say that becoming a data scientist is easy. You are challenging yourself to embrace a brand new way of creative thinking wherein you will have moments of self-doubt and struggle. Just like learning any other skill, learning data science also takes time. But, it is an achievable goal for almost anyone who’s willing to put in the effort and time. You may find many websites which try to push people into learning data science by citing it as an easy skill to master. On the contrary, data science is one of the most difficult skills to master and excel at. It is more of practice and experimentation than a guide that needs to be followed.
The experience of learning data science won’t be the same for everyone who takes on the challenge. For instance, you are likely to have great advantage learning data science if you have had years of training in statistics and probability or if you are an inspiring mathematician or someone with a computer science degree. You will be starting on a better footing than someone starting from scratch with math, statistics, probability, and programming. But on the other hand, a person without that experience may also have advantages when it comes to leaning data science if they have traits like curiosity, problem-solving intuition, and creative thinking.
Programming, Math, Statistics, Probability, Quantitative analysis are what many people think when they think about pursuing a data science career. While those are important and build a technical foundation of a data scientist tool belt, the only skill that is important for learning data science is structured and analytical thinking. There is no straight rule of thumb that distinguishes people from who are fit for data science against the ones who are not. All of the data science skills including analytical thinking can be learned and mastered and there is no such inherent or innate data science skill that one must have.
Who should learn Data Science?
Having said this, professionals who wish to encash the opportunity of becoming a data scientist, here is an overview of all the essential traits that determine who should learn data science and why –
Data Science is for the Curious
We all are familiar with the age-old saying –“Curiosity killed the Cat”. However, when it comes to pursuing a data science career, curiosity could be the key differentiator in transitioning to a data science career. Remember those childhood days where we used to question our parents for everything and keep asking why. As we grow up, we avoid asking questions and ignore the curiosity within us. To become a data scientist it is very important to have the urge to know more and explore the “why” factor associated with everything. A “yeah, but…” person who loves to solve mysteries and lives for asking questions will become successful in mastering data science skills. A curiosity trait will make you an adaptable data scientist in all conditions.
Data Science is for the Creative
The biggest mistake professionals often make is confound creativity with arts i.e. only an artist, actor, painter, or a writer can be creative. Or they think that only people who make breakthroughs in science or win Nobel prizes can be creative. Well, this is not true. Organizations across the world rely on creative people who can help them innovate and survive the competition. Learning data science requires one to have an open mind while learning something new and imagining how they can use that new knowledge and apply it to a business problem they are trying to solve. A creative mind always enables faster problem-solving abilities and this is what data science is all about. It is not necessary that you have to be born with creativity but you can always enhance your creative skills.
Data Science is for the Passionate
Data science is rapidly changing with new advances in machine learning and AI so you need to be passionate to fight the changes and design the best strategy of combat. There are tons of data science resources available that provide updated knowledge about the latest trends and changes in the data science industry. The ever-changing data science landscape is an essential part of learning data science. You must always be ready to deal with it.
Anyone can do it
“Learning data science” seems to be the buzzword at the moment. So, it doesn’t matter whether you are a man or a woman; sweet 16 or fabulous 50; a designer or a mathematician; data science is for you. If you find the right mentored data science course, surround yourself with other datapreneurs, and work through several data science challenges rather than giving up, you can learn data science. It’s not about whether you can learn data science, but how you can learn, how you can stick with it. The experience of learning data science may vary from person to person, and you are a free bird to choose your own data science learning path.
What we have found at Springboard about successfully learning data science, regardless of how you want to go about it, is to have a data science mentor and a community around you while you are learning. To not learn data science alone. Learning data science is just like learning to play guitar: playing on your own is always fun but the real excitement an motivation comes by improvising with others.
The internet today gives aspiring data scientists unlimited access to tons of free data science resources. However, access to content alone is not enough to build up the motivation required for learning data science; it’s the people connected through the content that make learning data science fun and challenging. That’s driven how Springboard has built the mentored data science track. You’ll see that our students come from diverse backgrounds and are successful in learning data science under the guidance of a mentor and launching data science careers.
If you are all set to fully immerse yourself in learning data science, check out Springboard’s Data Science career track. We follow a project-based curriculum and 1-on-1 mentorship to help you become a data scientist.