Great point! I remember reading an international comparison of broadband speeds and, surprise!, the leaders were tiny countries. I am sure one can find many other examples.
Another point: JavaScript jobs may be related with frontend development, including Angular and what not. Scala jobs may be related with big data, including Spark and what not. Learning the languages (a couple of weekends) means nothing. Some other things to consider are technology stacks, career paths, additional knowledge required in role descriptions, etc.
In particular, in frontend and big data there’s some new hotness every few months, knowledge becomes outdated fast. Best advice has always been “do something that you enjoy”, because in the end that joy may be the only thing you get.
Stefano Miccolisays:
Another point is that with small populations or “skewed” distributions, the median is a more significant figure than average. The average of [10 11 12 80] is 28.25, but its median is 11.5
I fully agree with the article. Statistics can be even more misleading as people tend to chase form over substance.
Moreover, while the study might show a _correlation_ between Rust and higher salaries, in no way does the study point towards _causation_. Maybe people programming in these languages earn high salaries because some other attribute they posses (being early adopters, understanding new tech quickly) goes hand in hand with TypeScript or Rust. But in no way does that mean that repeating what they did will yield the same results.
Even if we override the whole correlation-causation argument, we are left out with a typical portfolio theory trade-off: in order to increase your profitability (earn more per year) you also have to increase your risk profile (place your “bet” on a hyped tech that might as well be gone or regress to the market average in 3-5 years, for all we know).
As a conclusion, I think having a practical, solution-seeking, non-dogmatic mentality to technology is better correlated with high income than a specific programming language. People who ask themselves “What’s the right tool for the job in this context?” tend to earn more than those who think that just because they have a Go/Rust/TypeScript hammer everything else has to be a nail.
Great point! I remember reading an international comparison of broadband speeds and, surprise!, the leaders were tiny countries. I am sure one can find many other examples.
I would suggest C + malware expertise…
You wrote “nice” when you meant “niche”.
I saw that also, but didn’t think of “niche.” Niche catch.
I did. Thanks.
Another point: JavaScript jobs may be related with frontend development, including Angular and what not. Scala jobs may be related with big data, including Spark and what not. Learning the languages (a couple of weekends) means nothing. Some other things to consider are technology stacks, career paths, additional knowledge required in role descriptions, etc.
In particular, in frontend and big data there’s some new hotness every few months, knowledge becomes outdated fast. Best advice has always been “do something that you enjoy”, because in the end that joy may be the only thing you get.
Another point is that with small populations or “skewed” distributions, the median is a more significant figure than average. The average of [10 11 12 80] is 28.25, but its median is 11.5
I fully agree with the article. Statistics can be even more misleading as people tend to chase form over substance.
Moreover, while the study might show a _correlation_ between Rust and higher salaries, in no way does the study point towards _causation_. Maybe people programming in these languages earn high salaries because some other attribute they posses (being early adopters, understanding new tech quickly) goes hand in hand with TypeScript or Rust. But in no way does that mean that repeating what they did will yield the same results.
Even if we override the whole correlation-causation argument, we are left out with a typical portfolio theory trade-off: in order to increase your profitability (earn more per year) you also have to increase your risk profile (place your “bet” on a hyped tech that might as well be gone or regress to the market average in 3-5 years, for all we know).
As a conclusion, I think having a practical, solution-seeking, non-dogmatic mentality to technology is better correlated with high income than a specific programming language. People who ask themselves “What’s the right tool for the job in this context?” tend to earn more than those who think that just because they have a Go/Rust/TypeScript hammer everything else has to be a nail.