3.4.1 Employed Data Scientists

About 30% of or survey respondents would call themselves “Data Scientists” with about another 20 percent calling themselves either “Scientist/Researcher” or “Software Developer/Software Engineer”. So about 50% of our survey respondents fall in these three categories with the other 50% in other roles.

3.4.2 ‘Learners’

The Kaggle survey asked respondents if they were learning data science and their student status. 73% of the respondents who said they were learning data science are enrolled in an academic program.

55% of all respondents who said they are learning data science said they are “focused on learning mostly data science skills” with the other 45% saying that “data science is a small part of what I’m focused on learning”.

The ratio of respondents who said they are “focused on learning mostly data science skills” remains the same at about 55% regardless of whether or not they are enrolled in an academic program.

3.4.3 Learning Platform Usefulness - ‘Learners’

‘Learners’ think that the top 3 best ways to learn data science are through Courses, Projects and College with Arxiv and YouTube coming in 4th and 5th respectively.

3.4.4 Learning Platform Usefulness - Employed Data Scientists

Employed Data Scientists agree with unemployed ‘Learners’ that Projects and Courses belong in the top 3, but put College in 5th place (vs. 3rd). They also include Tutoring and SO (Stack Overflow Q&A) in their top 5 with SO coming in 2nd place. YouTube (learner’s 5th choice) comes in 14th place for employed Data Scientists and Arxiv (learner’s 4th choice) is 8th among employed Data Scientists.

Another interesting difference is that the importance of Friends to learning data science is much higher among employed Data Scientists with about 46.5% saying that Friends are “Very useful” and 97.5% saying that Friends are either “Somewhat useful” or “Very useful” vs. ‘Learners’ who put Friends at absolute bottom of their list with only 17.6% saying that they are are “Very useful” and 82.4% saying that Friends are either “Somewhat useful” or “Very useful”.

This may indicate a need to create a more robust community for Data Science ‘Learners’, who may feel somewhat isolated in their studies vs. employed Data Scientists who presumably have more established work and social networks that involve Data Science.

3.4.5 Job Skills Importance to ‘Learners’

‘Learners’ put Python at the top of their list of Job Skills with 63.6% of respondents saying that it is “Necessary” and 99% saying it is either “Necessary” or “Nice to have”. Only 1% said it was “Unnecessary”. R is surprisingly further down the list with only a little more than half as many respondents saying that R is “Necessary” compared to Python at 34.7% but many more agreeing that it is at least “Nice to have” for a total of 95% in favor of learning R which is just slightly less than those in favor of Python.

Surprisingly “Data Visualization” comes in only slightly above R with 39% saying that it is “Necessary” but actually slightly lower in terms of overall importance with 8% saying it is “Unnecessary”.

3.4.6 Work Tools Frequency

Not surprisingly I guess, Python is also high on the list of tools that working Data Scientists use with 75.4% of users saying that they use it either “Often” or “Most of the time” and only Statistica, SQL and Unix edging it out for the top 3 slots. What is surprising is that two of the the top three tools used in the field aren’t even on the list of Job Skills ‘Learners’ were asked to evaluate.

R comes in slightly lower than Python with 63.6% of users saying that they use it either “Often” or “Most of the time” but the difference between R and Python is less in the field than what ‘Learners’ seem to think is most important.

3.4.7 Work Methods Frequency

The big surprise here is that Data Visualization is at the top of the list. With nobody saying that they use it “Rarely” and only 8.5% saying that they only use it “Sometimes”. 91.5% say they use it “Often” or “Most of the time”. It is by far the most frequently used method or tool for working Data Science Professionals with Statstica as the next runner up at only 80% by comparison. Remember that only 38.8% of ‘Learners’ said that they thought Visualizations were a “Necessary” job skill to learn!