It’s right there in the title, ‘Data Science’. Were ‘Data’ & ‘Science’ the kind of words you heard that got you excited to grow up as a kid? Probably not, nevertheless, it’s still a huge field that’s growing even more every day, with so much untapped territory that essentially only evolves as human psychology and behavior does.
Data science, data analytics, machine learning and all its other synonyms, is a field that in effect, literally translates how people behave, think and respond, into numbers. It then analyzes those numbers and comes up with strategies and effective predictions on what to do to get consumers to invest in you and your product. I mean who wants that right?
So, here are 5 reasons why we think you shouldn’t take a course or learn data science and machine learning.
Money can’t buy happiness, and data science is definitely a lucrative career due to the scarcity of available data scientists paired with a high demand for them by employers. So if you’re looking to be happy then look away. However, if you’re looking to make money, then this will interest you. It would be good to know that on average, data scientists make around 3 times as much as other professions do. For 2021, Data Science is listed on the top 10 best paying jobs. But of course, getting paid well always means requiring to put in a lot of work. A salary survey in Dubai showed that a Data Scientist can earn between 30K-45K Dirhams a month, but again, I mean who wants that right?
- Responsibility & Recognition … Ugh
Do you really want to be the “go to” person in a company and have management and senior stakeholders come to you and ask for your analysis on how to move forward and make decisions? Or even hold a prestigious place among the ranks? Wouldn’t you just rather sit quietly and not have to interact with the bosses that get to decide who to promote? Because being a data scientist means that the nature of your role is to make actionable data-driven decisions and forecasts that push the product and company in the right direction. You get more responsibility, more attention and more people listening to what you have to say. I’m sure that’s not what you’re looking for.
- Who Wants Options?
When you go to a restaurant, do you really want a menu full of options to satisfy your various cravings and have you take your pick, or would you rather just have a standard menu with burgers, fries and pizza? Now this really applies to new professionals to the field, if you actually still end up deciding to learn data science after this, but most definitely still applies long after you’ve become an expert. Data is everywhere, and it has never been more in demand than the present. Pick your preferred industry, whether it’s the e-commerce industry, aviation, tech, healthcare, governmental, or basically any industry. They’re all looking for data scientists to help them improve their processes, understand their markets and consumers better, and make the right choice. The biggest companies in the world like Oracle, Facebook, Amazon, Google, Microsoft, Accenture, Uber, JP Morgan Chase are always scouting for data scientists. This means that unfortunately, you most likely have extremely strong chances at joining the company of your dreams.
- Why Join the Future?
At the heart and core of data science, is human psychology. Sifting through, organizing, and interpreting large amounts of information that are based on people’s behavioral patterns. People are now always connected to their devices at most times of the day, meaning that there has never been more information provided than now, and the future and success of any company is built around always keeping up with new trends and always understanding the ever-changing behavior of people. So really, getting into data science means you’ll be ready for the future, with artificial intelligence, machine learning and the principles of how to stay relevant and how to ensure profitable and effective planning. But hey, who cares? There’s no time like the present, right?
- Finally, No One Likes the Smartest Guy in The Room.
Data Science, two words that entail a whole lot more. From working with Big Data and Artificial Intelligence, programming and coding, recognizing trends and gaining the best insights from information, becoming a wiz at math and statistics to visualization and communication. You’re practically a walking computer and you’ll probably be one of the smartest people in a room, unless you’re at an astrophysics convention talking about the theory of relativity and singularities.… sorry. But that doesn’t go to say that it’s not an art. It takes a lot of out of the box thinking and creative approaches to see data in a way that provides insight
There are a number of reasons why you shouldn’t invest in your mind and career and plunge into the world of data science, but if for some reason you’re still interested and ready to begin that journey ..