‘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 an 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 article, we’ll share the top skills that will make you successful in this super-competitive field.
We’ve also created a very cool and interactivePowerBI dashboard, so if you prefer to analyze the data yourself, We’ve got another article where we make a comparison between the last 3 years, In this article, we will focus on the year 2020. In 2020, our study portrays a data scientist’scollective image as a male (71%), who is bilingual, has been in the workforce for 8.5 years (3.5years 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 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 PowerBI 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.
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 continuing to do so. 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 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 occupations and titles 1 and 2 jobs ago. Two positions prior to their current role, the average data scientist in our sample were either already a Data Scientist (29%), 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 Bachelors degree or higher.