What is the correct job title?

Question

R

Hello.
Recently I talked with a friend who claims that the popularity of the R language is now on the rise.
Tell me, is this really so?
I tried to find at least one vacancy related to the R language on HH. I searched for the phrase: R programmer. But I did not find anything. What is the correct name for this position?

Answer 1

It is on the rise (again) abroad, usually used by data scientists. The rise is mainly due to the hype around data analysis, machine learning and big data. R is very good for rapid prototyping on a small dataset, or already for "final" analysis and visualization, again on a small to medium dataset that has been pre-processed and cleaned. Many libraries related to mathematical statistics, machine learning, data analysis, visualization. Oracle promised to insert the ability to write R storages into its database, but I didn't see if they did.
At one time I took courses on Coursera on data analysis, I liked R as a medium as a language. Now there is a competition between R and python with libraries like numpy, pandas, sklearn and so on for the title of the best tool for data analysis. Plus there are vendor tools like SPSS that offer the same capability.
As for vacancies in your region, they are, but they are few. Here is an example https://hh.ru/vacancy/20496633?query=%D0%B0%D0%BD%...
I would not expect that in Russia in general, and even more so outside of Moscow, you can easily find a job as a data analyst without real experience and success in this area. But, I repeat, the profession of Data Analyst is now very popular abroad and the R language is often considered one of the necessary tools that he must master (see note about python).

Answer 2

The R language exists, it is quite fast, but it is rather narrowly focused, and seems to be extremely unpopular for mathematical calculations. Your friend is wrong, the popularity of the R language does not go, but fluctuates around zero. This is a problem for many developers - to think that the technology / language they work in is top, popular, best, etc.

Answer 3

There are a lot of technologies from the 90s that were really popular and convenient when the language ecosystems were not yet developed.
Compared to general-purpose languages, of course, R was very convenient, but now is not the 90s.
Now any general-purpose language allows you to do the SAME, ALSO simple (through libraries and frameworks), but at the same time it has more flexibility, performance, and solves a much wider range of tasks.
If you ALREADY know R, then you can use it and solve problems on it, but if you are just STARTING to solve mathematical problems, then it is better to avoid this language.
R has been great at solving problems in the past, but in 2017, programmers hardly need it. Maybe housewives who need something more powerful than Excel, who, for example, climb into advertising targeting. Even so, it is better for programmers to immediately sharpen solutions using -> python, node, rock, or at least java.

Answer 4

he is very narrow, well, he had half a percent, it still became less than a percent, what do you expect then?

Answer 5

Although R is a programming language, in fact it is not an alternative to the conditional python, but an alternative to Excel. The R + RStudio bundle allows you to do everything that Excel does much easier and faster than with any data set, plus a lot of things from above like machine learning (which is no longer exotic and becomes a working tool), parsing data from different sources and many visualization options data (by the way, there is nothing like the ggplot2 package in the same python, although the transfer project was but it seems to have stalled).
It is clear that most employers have not heard of any R, and instead of R they will write about Excel or, at best, about big data, machine learning or data "cleaning". I think it's a good idea to search for vacancies by querying Excel VBA - such employers, as a rule, have already reached the ceiling of Excel capabilities, and perhaps they no longer need Excel. Or, on the other hand, look for jobs related to data visualization (it really depends on what you specialize in more, I personally came to R precisely because of its data visualization capabilities).