The Sexiest Job of the 21st Century Isn’t “Sexy” Anymore
Are you a data scientist?
If yes. Well, then you must be feeling pretty damn “sexy”.
Sexy doing the hottest job of the century. Sexy being in the highest position, Sexy of being considered as a most demanded person. Sexy dealing with glamorous artificial intelligence, machine learning, big data, and all. Sexy earning around $13K to $120K per year. Sexy living your dream life while doing your so-called dream job.
Well, I hate to break it to you but you aren’t… sexy anymore.
It was long back 8 years ago in 2012 when Harvard Business Review posted the article called “data scientist” as the sexiest job of the 21st Century.
But that’s not the case anymore.
According to Financial Times’s recent study, “Data scientists are spending an average of 2 hours a week looking for a new job.” A study by Stack Overflow found that 13.2 % of data scientists were looking for a new job If you search for “data scientist” on LinkedIn, you might be surprised to see how many of these pros have “seeking new position” headlining their profile.
The trends are changing nowadays. The demand is no longer the same as before and data science is losing its charm.
But if being a data scientist is considered cool or sexy then — Why the hell are people leaving it?
Being the sexiest job does not mean everything about it is hot and sexy. Many aspects of Data Science are gruesome and sometimes scary.
Here are a few reasons data science (ever considered a sexy job) is losing its charm :
#1 People Doesn’t Know What Actually Is Data Science
What is data science?
It’s a simple question but answers are often very confusing.
Well, if you think about this, ‘data science’ is not something which we can refer to as funny but due to its confusing concepts, people have made n-number of inside jokes on data science:
- Data science is 80% data preparation, 20% complaining about data preparation.
- People refer to data scientists as a data analyst who lives in California or a statistician who lives in San Francisco or who is statistics on a Mac.
Here’s the truth…the industry doesn’t work that way.
There are so many things to use to do a data science project or anything close to what we find in online science competitions.
“I would consider the data scientist to be a misunderstood job,” said Kate Cascaden, technical recruiter in data science. “Coding languages are sexy, data principles are interesting and intriguing, and they will absolutely affect the way technology is developed in the future. But it is also a market that is not fully understood by many organizations.”
Many people think of data science as an industry that only performs certain tasks but that is not true. A data scientist is a topic that combines many different tastes of work.
#2 Expectation vs. Reality — Here Lies A Wide, Wide Gap!
One of the most common issues in the data science field is the huge difference between expectation and reality. There’s an ever-widening gap between what was expected by data scientists and what work they actually do within the industry.
“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.” — Dan Ariely
This quote is so true. Many people are urging you to get into the science of data because it’s all about solving complex problems with new learning algorithms that make a huge impact on a business. They think that being a data scientist is sexy and it will make them look cooler.
But that’s not the case. It’s not what it looks like.
The fact that people don’t actually know exactly what data science is, leads them to make different expectations from the industry and when they enter the industry. Boom!! Boom!! And just like that, all their expectations are crushed.
And because people’s expectation isn’t equal to the reality that’s the main reason why so many data scientists leave.
#3 Lack of Upskilling for Data Science Professionals
“There is a saying, ‘A jack of all trades and a master of none.’ When it comes to being a data scientist you need to be a bit like this, but perhaps a better saying would be, ‘A jack of all trades and a master of some.’” ―Brendan Tierney
We all love new challenges, don’t we?
Many would disagree with the fact that the field of data science is ripe for these challenges given the rapid pace of development.
Considering technology is rapidly evolving, the necessity for a company to rent a knowledge scientist is additionally evolving. With the increasing demand for emerging technologies, businesses are trying to find data scientists to be skilled with new-age technologies instead of older programming languages like R, Ada, C, Haskell, etc.
Currently, companies are searching for newer skills like data visualization, machine learning, to call some, to form a more informed decision during this competitive landscape. Data scientists now need to know advanced mathematical tools and methods for calculating and integrating large data sets.
So, as the skills requirements are increasing, it’s becoming very hard for people to get into this field, which, in turn, creates a shortage within the market.
There is a lot of scope in this field but the lack of people with actual skills needed is snatching the title of the ‘most promising job’ and ‘sexiest job’ and many people are walking away from it.
#4 You Can’t Fake ‘Sexy’
Many might argue with the fact that you can’t fake ‘sexy’.
Either you are or you aren’t — you have it, or you don’t.
And even if some organizations don’t exactly know how to best tap the talent of their data scientists, but if those professionals are the “real deal,” that appeal can’t be denied.
“Data scientist is still the sexiest job of the 21st Century,” insisted Crawford. “The professionals in this field are absolutely amazing and extremely intelligent. In what other fields can you be part detective, part innovator, and, depending on who you work for, part international spy.”
The role of a data scientist has changed dramatically which in turn affected the whole industry and its people. A lot of companies misrepresent ‘data science’ when they really are looking for is data analysts, data engineers, or business intelligence, analysts.
“Many companies need to stop looking for a unicorn and start building a data science team”, says the CEO of data applications firm Lattice.
#5 People Aren’t Willing To Wait
The data scientist is a job that requires a lot of hard work, consistent efforts, persistence, and most importantly patience.
PATIENCE…and that’s where the main problem arises.
Our generation lack patience skills, they need everything according to their expected timeline, they need results immediately without doing the actual hard work. It’s like they want a pizza without putting any effort to order or without having the patience to wait for its delivery.
And that can’t happen.
If they want a pizza then they gotta put an effort to make a phone call to order it and they gotta have to wait for it to be delivered.
It requires both: Hardwork+Patience.
There is so much to learn and no one is willing to do the hard work. It is very difficult for anyone to start with basics and excel in this field. This requires consistent efforts over time and people aren’t patient.
So, should we still be calling the data scientist the sexiest job out there?
“I would say ‘yes,’ but it depends on how and why you are using it,” said data science recruiter, Frazer Spackman, at Huxley Associates. “If you are working for a business where data science is integral to the business product, vision, and success, then this statement is true. But a lot of companies are misrepresenting ‘data science’ when really they are looking for data analysts, data engineers, or business intelligence analysts, in which case, the statement above doesn’t apply.”
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