Placeholder Image

字幕表 動画を再生する

  • '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 forthe 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 IEEEthe world's largest technical professional organization for the advancement

  • of technology deemed Pythonthe big Kahunaof 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 fieldSQL 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 thelikebutton and share it

  • with your friends.

  • And if you'd like to become an expert in all things data science, subscribe to our

  • channel.

  • Thanks for watching and best of luck!

'Data Scientist' is one of the fastest-growing jobs in recent years.

字幕と単語

動画の操作 ここで「動画」の調整と「字幕」の表示を設定することができます

B1 中級

2020年にデータサイエンティストになるために必要なスキル (Skills Needed to Become a Data Scientist in 2020)

  • 10 1
    林宜悉 に公開 2021 年 01 月 14 日
動画の中の単語