10 Reasons to Become a Data Scientist

Fat bikes are the newest trend sweeping not just the nation, but the world. Fat bike has been around for about a decade, but newer, slicker models are enticing riders of all ages to give fat bikes a try. These larger, heavier bikes are designed to ride on rough terrain where there may not be a bike path or road previously established. Read on to learn ten reasons to ride a fat bike.

• 1. The Job Outlook

Don’t expect this bubble to burst anytime soon. According to a report by McKinsey & Company, by 2018, the U.S. will have anywhere from 140,000 to 180,000 fewer data scientists than it needs. And the shortage of data science managers is even greater. Roughly 1.5 million data decision-making managers will be needed by 2018. At some point, the frenetic pace at which employers pursue data scientists will slow down, but it won’t happen anytime soon.

• 2. Growing Demand

Data Scientist is the job which is creating a hype, by its demand all around the world. According to a report by McKinsey & Company, by 2018, the U.S. will have data scientists around 140,000 to 180,000 fewer data scientists than it needs. The demand for data science is increasing, while the supply is too low. India requires over 200,000 data scientists by 2018 compared to engineers and chartered accountants. So why to wait, become one of them and be in demand.

• 3. Unbeaten Salaries

According to the Glassdoor, in 2016 data science was the highest paid field to get into. According to their findings, the national average salary for a Data Scientist is INR 6,50,000 in India and the national average salary for a Data Scientist is $1,20,931 in the United States coming to Europe, national average salary for a Data Scientist is €52,000. These salaries are much higher compared to other jobs.

• 4. The Management Salaries

Data science managers can earn almost as much – and sometimes more – than doctors. Burtch Works reveals that Level 1 managers earn a median annual base salary of $140,000. Level 2 managers make $190,000, and Level 3 Managers earn $250,000.  And that puts them in pretty good company. According to the BLS, pediatricians, psychiatrists, and internal medicine doctors earn a median annual wage between $226,408 and $245,673. So without years of med school, residencies, and medical debt, you might earn more than the person who holds your life in his/her hands on the operating table. Cool. Scary, but cool. 

And when you factor in median annual bonuses, data science managers out-earn many surgeons. Median annual bonuses for Level 1, 2 and 3 managers are $15,000; $39,900; and $80,000, respectively.

• 5. The Sexiest Job in 21st Century

The prestigious Harvard Business Review hailed data scientist as the sexiest job of the 21st Century. How on earth is that possible? Are data scientists suggestively dangling the data in front of their employers? Are they whispering sweet algorithms in their employer’s ear? No (at least I don’t think so), but some of them work with cool startups, and also mammoth companies like Google, LinkedIn, FaceBook, Amazon, and Twitter. In essence, their sex appeal lies in the fact that everyone wants them, but they’re hard to acquire.

• 6. Evolving Career

Data Science is evolving quickly because of the increasing demand of data around the world. Data scientists have a wide variety of skill sets that can leverage data and information to help organizations to make better strategic decisions. They get exciting opportunities to work and experiment with data to come up with the suitable solutions for the businesses. There are many new exciting fields are emerging within this field including Big Data, Artificial Intelligence (AI), Machine Learning (ML), along with some newer technologies like Blockchain, Edge Computing, Serverless Computing, Digital Twins, and others that employ various practices and techniques within the Data Science industry.

• 7. The Experience Factor

“Experience” is probably one of the most common words found in a job description, and frankly, companies usually want employees with a ton of it. However, data science is such a relatively new field that Burtch Works reports 40% of data scientists have less than 5 years of experience, and 69% have less than 10 years of experience. So scroll back up to Reason #2: Salaries to match up the wages with the experience levels. Level 1 individual contributors typically have 0-3 years of experience. Level 2 individual contributors usually have 4 to 8 years of experience, and level 3 individual contributors have 9+ years of experience.

• 8. The Ease of Job Hunting

Because data scientists are in such high demand and the supply is so limited, organizations have recruiters solely dedicated to finding these professionals. While candidates in other fields are harassing recruiters and pestering hiring managers, as a data scientist, you merely need to let it be known that you’re looking for a job . . . or maybe, you’re just thinking about looking for a job. In fact, the need is so dire that even if you already have a job, recruiters will try to lure you away with a better compensation/benefits package. Let the bidding begin.  

Data Science is flourishing, it is being the most demanding job of 2018. Companies are desperately looking for Data Scientists. As Data Scientists are high in demand and the supply is low. E-commerce companies are not only the companies who are hiring the Data Scientists, today Data Scientists are being hired by the companies from almost every fields, in fact, many start-ups are relying on Data Science to go ahead.

• 9. You will work on useful things.

Data science is mostly about researching human behaviour. Doesn’t matter if you are working on understanding the user experience of online users or creating a chatbot or predicting stock prices… If you think about it, it all comes down to one thing: how humans act. I think researching and understanding how we as individuals and as a society work is one of the most important projects of the 21st century. As a data scientist, you can take part in that.

Note: of course, you can always find yourself in pointless, stupid or even in harmful data projects. But I’m pretty sure that your moral compass will guide you in the right direction.

• 10. You will be able to create your own products.

For practicing data science, you have to learn coding. And if you learn coding, (especially if you learn Python) as a bonus, you will also be able to build your own products – or at least the prototypes. I remember, my first “brilliant” startup idea was to create a website that compares news from the big news portals (like BBC, ABC or CNN) and can tell which one is the most credible. That was my first self-built prototype of my first own product idea. And even though nobody really ever checked my credible-news selection, it felt great that I had built it by myself.
If you learn coding, a whole new world will open for you… and even in the worst case scenario, you won’t really build your own product, “just” become a great data scientist. 🙂

Source: https://stantyan.com/