Essential skills in Data Science
What skills are important and what are prominent in Data Science? In the following article, we will classify Data Science skills into 2 main groups: A. 13 essential, basic skills that most experts in Data Science have & B. Group of skills standout features that most of the respondents didn't have but wanted to add.
Let's see!
The question Kdnuggets posed recently in polls is:
What skills or areas of knowledge are available that you can apply in your work or research?
What skills would you like to add or improve?
The list of 30 skills is compiled from articles and polls on the Kdnuggets site with 1500 votes - large enough to produce a reasonable result. On average, each participant votes possesses 10 basic skills and wants to add or improve 6.5 other skills.
1. Relevant skills that need and want to be added or improved in the field of Data Science
The chart to vote for the Data Science skills must have and wanted by Kdnuggets
Image source: Kdnuggets
The chart above shows key points, with the X-axis showing the ratio of skills required - the answer to the first question in the poll. The Y-axis represents the percentage of desired skills - the answer to question 2 of the vote.
The size of each circle corresponds to the percentage of people voting for the skill. Color, light shade represents the percentage of desire or ability to possess (red = strong / more than 1; blue = weak / less than 1).
In this section, there are two main groups:
Group 1 are the skills located in the rectangular area to the right of the chart. You will see more than 40% of voters have these skills with a Want / Have ratio below 1. We call them Key Data Science Skills. These are listed in Table 1 below:
Key Data Science skills, ordered in descending order of proportion.
Among these skills, Python and Machine Learning are the ones that are most wanted to add and improve (the respective ratios are 37% & 41%, respectively). The least developed skills are Excel - only 7% of people want to add or add this skill.
Group 2 is the skills on the left side of the chart, highlighted by a red border, showing less common skills (percentage of people with <30%) but growing and expanding ( Want / Yes ratio> 1). We call them Outstanding Data Science Skills (See Table 2).
Outstanding Data Science skills, ordered in descending Want / Yes ratio
Interestingly, despite the many opinions that Hadoop is on the decline, in this poll there are more people who want to learn Hadoop than people already know about it. Therefore, this skill is likely to develop in the future.
Among the outstanding skills, I do not mention Julia even though her Want / Yes ratio is 3.4%. The reason is because only 2% of people voted for it. This percentage is not enough to put it on the list.
2. Other Data Science skills
XGBoost, software engineering, Java, MATLAB, and SAS were in the 10-30% range of the respondents, but these are not developing skills because of the Want / Yes ratio <1.
Table 3: Other Data Science skills, sorted by Decreasing Have rate
Below are details of the voting charts with 2 ranks of skills in descending order of percentage.
The chart demonstrates the Data Science skills the reader Kdnuggets possesses
The third chart shows the skills that the reader wants to add or improve in addition to the existing skills.
The chart shows the Data Science skills that the Kdnuggets reader wants to add or improve (in red) against the Yes ratio (in blue).
As can be seen, the outstanding skills that Data analysts (Data Scientists) most want to add are Deep Learning, Tensorflow, Machine Learning and Python.
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Industry / freelance: 64.4%
State / non-profit: 7.2%
Education / training: 7.0%
Student: 14.3%
Others: 7.1%
National factors:
US / Canada: 37.9%
Europe: 28.3%
Asia: 19.3%
Latin America: 6.1%
Africa / Middle East: 4.8%
Others: 3.5%
The analysis in this survey is only the beginning, based on the popularity of the article, we will take a closer look at the relationship between skills with career type and location. the following articles. Besides, if you are interested in learning Data Analysis an important first step in the Data Science industry, then immediately register for the Nordic Coder course.