The market for Data Science has been growing
extensively over recent years.
As a result, the position of data scientist
has emerged as a truly attractive career path
option with an abundance of rewarding job
opportunities.
So, to help you stay at the forefront, we’ve
conducted an in-depth study on job offers
in the field of data science.
And in this video, we’ll share our insights
based on 1,170 job offers in the USA.
We’ve extracted valuable information of
the company offering the position, the required
educational credentials, and sought-after
work experience, as well as desired skills
and techniques involved.
If you are looking for a comprehensive guide
on how to enter the field, check out the description
below.
If you want to check the job positing situation
instead, let’s explore the intriguing findings
together, shall we?
We’ll start with the details of the targeted
companies.
The 1,170 data scientist positions in our
study were posted by 357 unique companies.
This is a positive sign, as:
First, the presence of many different companies
means the data is more likely to be a random
sample of the market and therefore not biased
towards the requirements or needs of a single
or few companies.
And second, this also shows that the website
is an active and popular job openings aggregator.
That being said, let’s take a look at the
distribution of offers against the size of
the company making the offer.
Here’s a chart of the number of openings
posted by companies with their respective
number of employees:
It’s easy to see that the majority of job
offers come from very big companies, with
more than 10,000 employees.
This could significantly skew our data towards
the necessities of big corporations.
However, looking beyond that, 823 of the total
1,170 job offers were posted by companies
that didn’t actually have a profile on the
website.
Therefore, their size hasn’t been determined
and is not present in the chart.
With that in mind, we can assume that bigger
companies tend to register on more employment
websites, while their smaller counterparts
do not engage as much.
So, these 823 offers could have been made
by companies small enough to not register.
Alright.
But what about the offers themselves?
Let’s analyze this!
First off - location
The jobs studied originated from 38 states
in the US.
Here are the top 12: California, Virginia,
Washington, New York, Massachusetts, Maryland,
Texas, Colorado, Michigan, Ohio, New Jersey
and Florida.
And here are the same states highlighted on
a map:
Okay.
Now that you have a good idea about the top
states by number of offers, let’s move on
to the job requirements.
…Starting with education.
When it comes to education, 544 job offers
stated that they require at least a Bachelor’s
degree, 367 – a Master’s and 50 were looking
for a Ph.D. While at the same time in 209
job offers, the level of education was not
stated.
As for the preferred fields of study, here
are the results.
The data was collected by extracting only
the first three mentioned fields.
Data science takes the lead, followed by Statistics,
Mathematics, Computer Science, and Engineering.
IT, Economics, and Physics are much less popular,
according to the numbers.
Okay!
Next up is work experience.
We categorized the years of experience in
these 2 categories: ‘years of experience
as a data scientist’ and ‘general work
experience.’
Bear in mind that in most job offers, general
work experience should be in a related field.
What we found out is that on average companies
demand that candidates have at least 4.2 years
of previous experience as a data scientist
and 5.2 years of experience in related fields.
How about programming languages?
Here are the most quoted programming languages
in the 1170 job offers (there may have been
more than one language per offer):
No big surprises here – Python is the most
popular one, as expected, followed by R and
SQL.
The other languages with a significant number
of mentions are Scala, Java, and C++.
So, if you’re looking to advance your programming
skills to become a data scientist, 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!
Back to our research.
We’ve also done keyword analysis on the
description of the job offers and extracted
the skills and machine learning techniques
that are cited the most.
Here they are:
As expected, the most important skills to
have are Machine Learning, Statistics, and
Python programming, while the most in-demand
machine learning techniques are Deep Learning,
Clustering, and Natural Language Processing
(NLP).
The last parameters that we extracted were
Database/Cloud skills, data visualization
techniques, and whether there is an emphasis
on communication or not.
Let’s see what we’ve discovered!
The numbers show you should definitely consider
adding Spark, AWS, or Hadoop to your data
scientist toolbelt.
Regarding data visualization, it all comes
down to Tableau and Power BI.
Tableau was mentioned in 228 job offers, whereas
Power BI in 79.
Are communication skills of major importance?
That was true in 368 offers, while in the
rest 802 there was no mention of communication
or teamwork at all.
Now, as promised, let’s analyze the prior
work experience with respect to the education
required.
Here is what we found:
As you can see, there is no real significant
difference between the preferred work experience
for the different degrees.
However, there are two very important factors
to consider here:
First, the sample size is not large, especially
for the Ph.D.
Second, this data applies to candidates with
a degree that is the minimum requirement.
In fact, there were no job postings that did
not require university education.
As in any other industry, holding a Ph.D.
lowers the minimum required experience.
However, not dramatically so, especially having
in mind that a PhD takes several years to
complete.
So, let’s look at how the company size affects
the experience required.
For this analysis, we have grouped the companies
into 5 categories: small (1 – 100 employees),
medium (100 – 1,000 employees), big (1,000
– 10,000 employees), sizeable (10,000+ employees),
and those with No size data.
It is very important to remember that the
sample size here is rather small.
Quite surprisingly, it looks like the smallest
companies have the highest requirements for
experience.
Apart from the sample limitation, we can assume
that smaller companies have a limited number
of employees and, to expand and become successful,
it needs more experienced professionals.
The sizeable companies, in contrast, may not
necessarily need an experienced individual
but someone they can train to become a useful
tool for the company in the future.
And we’ve arrived at the last piece of analysis
– what companies of different sizes require
as a level of education.
Due to the small samples, we have decided
to summarize the data in a table, rather than
a graph.
Smaller companies don’t really look for
PhDs and prefer Master degree holders.
At the other end of the spectrum, the bigger
companies have somewhat more balanced requirements
with an approximately equal number of positions
asking for either a Bachelor’s or a Master’s
degree.
Alright!
That was our compelling look at a sample of
1,170 job offers for the position of data
scientist.
Hopefully, you have found some of this information
useful and advantageous for you in your path
to landing your dream data scientist job.
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Thanks for watching and good luck!
