What are you basing this on? Senior software engineer jobs are a lot easier to come by than data scientist jobs and from what I've seen, pay better than the average data scientist job as well.
If it had been as difficult then as it is now I would probably have chosen software engineering.
Honestly, I feel software engineering might be better anyway as it's much easier to demonstrate value building features and shipping products rather than endless analysis and questionable models.
Current Software Engineer, for full disclosure, pondering how to move away from the prevalent web dev job market where I currently reside. Data science seems to pay on par.
There's nothing wrong in data science itself, just like there's nothing wrong with mortgage. But the current trend of software engineer/ non-software engineer moving into data-science is not sustainable. Things will break before it's fixed again, I've always considered myself a software engineer first and foremost, just with some extra machine learning/stats knowledge, and I'm glad to be out of that position now as it looks like we're in for a reckoning soon.
In my experience from my old employer...clients like Google get billed $120/hr for SQL analysts' services; ten years ago, staff earned $20/hr or a little more, and today, they've replaced almost everyone with offshore employees making $3-4/hr.
That’s interesting. I’m at one of F/G and a lot of the data scientists want to go the other direction to software engineering because we receive about 60% of the RSUs that they do. A few people on my team actually did switch; they said they found the data science work more interesting but an additional $40-100k per year can make a really big difference over the long run.
Facebook and Google "data scientists" (meaning those who hold the title) are really more like analysts -- they analyze data to inform decisions and use a lot of SQL. They make prototype models (usually based on less cutting-edge techniques) that get passed to engineering teams if they become worthwhile to scale/formalize. These folks get paid less than SDEs usually.
The other type of "data scientist" is basically an SDE (maybe SDE-lite) with research-level ML skills. These get paid similarly (or higher in some cases) than SDEs. I believe Facebook and Google call these SDEs. Sometimes the term "applied scientist" is used to describe these at other companies as well.
At my company, Type A are called "Data Analysts", but at Google Facebook they're called "Data Scientists". Type B are "Data Scientists" at my company, but "Machine Learning Engineers" (or SWE-ML or some other combination) at Google and Facebook.
As a Type B, at my company, I'm on the same pay scale as the SWEs. The Type As are not.
What sorts of SDE positions do these data scientists go into? Are there any additional skills they pick up as part of the transition, or are strong Python/SQL skills enough?
If your job is working you too hard, with not enough pay, then people here get another job. It seems harder to high people with some experience at my company anyway. New college grads make 120k+ at top companies (we are a startup but not a unicorn, we pay a little more than that).