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!