It has been several years since the Harvard Business Review called data scientist “the
sexiest job of the 21st century”.
A lot has happened since then, hasn’t it?
New social media platforms Self-driving cars
Apps for ridesharing, food delivery, dating, and even face-to-face communication.
And of course, 2020 happened - the year we all wanted to cancel for a good reason.
Forced to stay home, our lives became even more digital than they already were.
The global pandemic hit hard and accelerated the transition to a world in which we work
from home, meet our colleagues over virtual coffee in Slack, and generate zettabytes of
digital data, which is then analysed by... data scientists companies need to hire.
As a result of these trends, leading companies became more data-driven than ever.
So, if there is one thing that didn’t change, it is certainly the demand for highly qualified
data professionals.
In this context, thousands of individuals around the world embarked on their journey
to learn data science and become data scientists.
And, without a doubt, if we had to rank career paths based on their appeal at the end of
2021, data science would most definitely land among the top 3.
As every year, we conducted our annual research on 1,001 data scientist LinkedIn profiles
to define who the typical data scientist is and what their career path looks like.
But before we start with the study, we’d like to announce our most exciting initiative
to date.
Starting on October 18th, we’re bringing back the free for a month initiative at 365datascience.com.!
That’s right - from the 18th of October until the 18th of November, you will be able
to access our newly rebranded platform and all our courses completely for free!
So, make sure you save this date on your calendar!
Ok.
Great.
Now let's get right into our main topic - the 1001 data scientist profiles we studied on
LinkedIn.
The numbers we obtained paint the following picture of the typical data scientist in 2021.
A male, who holds a Master's degree and works comfortably with Python and SQL.
Employed by a very large firm in the Technology sector, he has 6.2 years of prior working
experience and has been on the current job for about 1 year.
The typical data scientist in 2021 is expected to stay on their current job for 1.7 years.
and has changed companies around 2 times in the last 5 years.
Of course, we’re aware that this is a generalization, but it can be a useful one, as it gives an
idea about the profile of people working in the field.
Let’s examine the data in a bit more detail, shall we?
This year, the ratio of men to women is even higher (82% to 18% in 2021 compared to 71%
to 29% in 2020, which is a bit disappointing considering that in recent years companies
have committed to diversify their workforce and recruit people from different backgrounds.
What about degrees?
As an education platform, we are frequently asked “Do I need a university degree to
get hired as a data scientist?”.
The numbers clearly say “Yes, you do”.
97.2% of the individuals included in our study earned a university degree.
However, we observe one interesting trend.
The proportion of data scientists with a Bachelor’s degree grew from 12% in 2020 to almost 20%
in 2021.
And we’re not surprised.
With the ever-increasing access to online education platforms (including university
courses offered online), companies will likely prioritize technical skills over formal qualifications
(like Master's and Ph.D.) when selecting talent.
Python’s popularity in the data science field has continued to grow in 2021.
Almost 85% of the data scientists in our cohort use Python.
SQL is the other most popular tool coming in as a very close second (82%).
A considerable number of users continue to use R (64%), which over the last few years
lost some ground to the syntax-friendly Python.
Python, SQL, and R are the three most popular coding languages data scientists ‘speak’.
Now let’s shift our focus to a different aspect.
Workforce mobility in the data science field is a topic that has not been studied in detail
as far as we are aware.
The demand for skilled data scientists continues to be very high and we wanted to explore whether
this impacts how much time data scientists spend on the job (before switching companies
and starting new employment).
The median time data scientists spend on the job is 1.7 years.
In fact, more than half of the data scientists in our analysis (56%) changed jobs two or
more times in the past 5 years.
Unfortunately, we don’t have data that can allow us to compare such mobility with other
similar professions.
However, considering the amount of training and onboarding that is necessary to bring
someone up to speed and get them to 100% productivity, the mobility that we see poses the question
of whether this is efficient and effective for companies.
Perhaps Netflix’s strategy (shared by the firm’s CEO in his book ‘No Rules Rules’)
to overpay employees to keep them with the company for as long as possible is a viable
one considering the costs involved with training a new person every 18 months or so?
Alright!
That sums up the profile of the data scientist in 2021.
If you found our research helpful, don’t forget to hit the “like” button, share
it with your friends, and subscribe to our channel for more videos like this one.
And if you want to become a certified data professional, don’t forget that you can
get a full month of free access to our comprehensive online data science program, starting October
18th, so set a reminder.
Thanks for watching and good luck!