'Data Scientist’ is one of the fastest-growing
jobs in recent years.
It’s an exciting and highly paid career,
that presents you with tons of opportunities
for development.
What’s more, there’s still abundance of
positions as the supply of qualified data
scientists is yet to catch up to the huge
business demand.
So, what are the skills you need to become
a data scientist in 2020?
We’ve been doing this research for 3 years
now, and in this video, we’ll share the
top skills that will make you successful in
this super-competitive field.
We’ve also created a very cool and interactive
PowerBI dashboard, so if you prefer to analyze
the data yourself, the link’s in the description.
We’ve got another video where we make a
comparison between the last 3 years, which
we have also linked in the description.
In this video we will focus on the year 2020.
In 2020, our study portrays a data scientist’s
collective image as a male (71%), who is bilingual,
has been in the workforce for 8.5 years (3.5
years of which has worked as a data scientist).
He or she works with Python and/or R and has
a Master’s degree.
Now, let’s to focus on what you came here
for – the data scientist skillset.
You can’t become a data scientist without
a strong programming skillset.
And in 2020, general-purpose languages are
used more extensively by data scientists than
ever before.
According to our own annual research, 74%
of current data scientists are proficient
in Python, 56% use R, and 51% - SQL.
To say that Python’s popularity is rising,
would be an understatement.
Python is hands-down the preferred language
for statistical modeling by data scientists.
No wonder IEEE – the world’s largest technical
professional organization for the advancement
of technology deemed Python “the big Kahuna”
of programming languages!
But what do companies want?
Well, Python is more than just a fan favorite.
In fact, it seems to be very close to dominance
in terms of what employers are searching for,
as it is the language associated with the
highest salaries worldwide.
The demand for Python as a preferred skill
by employers is soaring sky-high.
Numbers don’t lie - 70% of F500 data scientists
employ Python.
Both Python and R have increased in popularity
over the years and F500 companies are reflecting
that in their organizations.
Moreover, Python is the number 1 programming
language in numerous industries that use advanced
analytics for their business and product development.
What about SQL?
SQL’s popularity is growing fast and it
almost catches up to the runner-up R. Today’s
businesses create quintillion bytes of data
on a daily basis.
That makes SQL a super-important tool in a
data scientist’s toolbox since it is critical
in accessing, updating, inserting, manipulating,
and modifying large volumes of data.
It also integrates smoothly with other scripting
languages like R and Python.
Besides, BI tools such as Tableau and Power
BI are heavily dependent on it, thus increasing
its adoption.
So, if you’re looking for great career opportunities
across numerous industries, you literally
can’t go wrong with Python, R, and SQL.
And if you’re a beginner eager to make the
first steps in your data scientist career,
the only thing left to do is start learning!
And we’ve got you covered.
We developed the ‘3-6-5 Data Science Program’
to help people of all backgrounds enter the
field of data science.
We have trained more than 450,000 people around
the world and are committed to continue doing
so.
If you are interested to learn more, you can
find a link in the description that will also
give you a special offer on all of our plans.
Alright!
Another interesting finding in 2020 is that
fewer data scientists are in their first year
on the job (13%) compared to previous periods
(25% in 2018 and 2019).
A few years ago, as data science had just
emerged, companies were recruiting professionals
with different backgrounds and training them
in-house.
As a result, in some cases, relatively junior
candidates were hired for senior data scientist
roles.
Our numbers show that as more people gain
experience in the field, first-year data scientists
account for a smaller portion of the total.
The idea that experience plays a bigger role
in recruiting is reinforced by the finding
that the average data scientist professional
in 2020 has been in the workforce for 8.5
years.
Therefore, in today’s job market one needs
to accumulate the necessary working experience
in an analytical position before they are
ready for a data scientist job title.
Maybe a data analyst position works best.
But what does the data show?
Our study examined data scientists’ previous
job occupation and title 1 and 2 jobs ago.
Two positions prior to their current role,
the average data scientist in our sample was
either already a Data Scientist (29%), an
Analyst (17%), or worked in Academia (12%).
The figures change when we look at the positions
our cohort occupied immediately before entering
their current role: data scientist (52%),
analyst (11%), a researcher in academia (8%).
What about education?
The large majority (95%) of current data scientists
have a Bachelor’s degree or higher.
Out of those, 53% hold a Master’s degree,
and 26% - a Ph.D.
We can say that a person needs to aim at a
second-cycle academic degree, however, it
is also true that a Bachelor’s can get you
the job as long as you have the technical
skills and preparation required.
In general, 19 out of 20 data scientists have
a university degree.
Cool.
How about the area of studies data scientists
pursued?
Which degrees improve a candidate’s chances
of becoming a data scientist?
Considering our study, 55% of the data scientists
in the cohort come from one of three university
backgrounds: Data Science and Analysis (21%),
Computer Science (18%), and Statistics and
Mathematics (16%).
There are fewer representatives of Economics
and Social Sciences (12%), Engineering (11%),
and Natural Sciences (11%).
All of these are technical courses that prepare
graduates for the quantitative and analytical
aspects of the job.
Alright!
We’ve learned quite a lot!
So, let’s summarize the most important findings
describing the typical data scientist career
path in 2020:
• Python is undoubtedly the most popular
coding language in the field
• SQL is gaining ground closing in on R
• Frequently the previous job data scientists
had was an analyst position
• 95% of data scientists have a Bachelor’s
degree or higher
• A Data Science, Computer Science, or a
Statistics and Mathematics degree gives the
best chance for a data scientist career
They say that ‘if you don’t know where
you are going, any road will take you there’.
In this case, things are a bit different.
If you know that you want to become a data
scientist, it will be beneficial to study
the career path of others who have taken the
data scientist career path and learn from
their experience.
We hope that this video was useful and will
guide you in the right direction if you decide
to pursue a data scientist career path!
If you enjoyed this video, don’t forget
to hit the “like” button and share it
with your friends.
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channel.
Thanks for watching and best of luck!
