[deleted]
Demand and Salaries for Data Scientists Continue to Climb
31–40 of 49 posts
Re: Demand and Salaries for Data Scientists Continue to Climb
#32Earlier quoted context omitted.
Data Engineer role is about building big data/streaming pipelines for data and often DevOps aspects of keeping such pipeline deployed and online. A boring, dead-end job. Avoid. Make yourself both ML/DL master and SWEng and you'll be doing extremely well.
You know that's usually the hard part of ML projects, right? It may be boring, but it also tends to be the less least replaceable component.
Yes, and there is zero prestige within company, awful lot of high-pressure work, no control over bugs in infrastructure pieces that tend to blow up unexpectedly in production, getting stuck on a certain stack that tends to age badly (who remembers Hadoop or Spark 1.3 these days?), making one quickly replaceable by younger folks with the latest hyped tech, small understanding of the data science part, no joy from constructing great algorithms either. It's a needed job of course; it might pay well at this very moment but it's a perfect target for automation once latest cognitive automation research bubbles down to production.
If you want to shine, do Deep Learning (research if possible), low-level distributed systems you have control of as an author of an important piece of infrastructure or the actual data modeling and predictions.
Re: Demand and Salaries for Data Scientists Continue to Climb
#33Earlier quoted context omitted.
That’s why you become a data engineer and get the best of both worlds. If you can market yourself to a company as a “full stack data developer” you will make more money than either category
"data engineer" is often considered a lower prestige title than data scientist. "Data scientist" is a title recently thrown around a lot for positions that used to be called "data analyst", with no strong ML or SWE ability required. Amazon's title for scientists with strong ML engineering ability is called "Applied Scientist" and it's paid significantly higher than SWE
a title recently thrown around a lot for positions that used to be called "data analyst"
Agreed. Maybe this is different in different markets but in London the vast majority of "data scientist" positions advertised are really PowerBI, Excel, etc. If there is any ML it is just to feed data into a black box model. If you were both smart and lucky you might be able to sneak R in by the backdoor and start doing actual data science, but it would be an uphill battle.
Re: Demand and Salaries for Data Scientists Continue to Climb
#34Hands off my data, scientists!
Re: Demand and Salaries for Data Scientists Continue to Climb
#35Compensation may be going up, but at top tech companies, software engineers still make significantly more than data scientists for the same level (twice the RSUs). I’ve noticed at non-tech companies, the reverse seems to be true: data scientists make slightly more than software engineers.
(Disclaimer: generalization ahead) That might be because they're starting to get hip to the fact that too many data scientists struggle to produce professional-level code, forcing you to pay a software developer to create the actual deliverable from their prototype. At that point, why not just hire a really bright software engineer who can code well and knows how to work with data?
I'm not sure it's easy for a software engineer to develop a model, it's quite an orthogonal skill, you need a solid grasp on mathematics and especially statistics.
Re: Demand and Salaries for Data Scientists Continue to Climb
#36Earlier quoted context omitted.
(Disclaimer: generalization ahead) That might be because they're starting to get hip to the fact that too many data scientists struggle to produce professional-level code, forcing you to pay a software developer to create the actual deliverable from their prototype. At that point, why not just hire a really bright software engineer who can code well and knows how to work with data?
I'm not sure it's easy for a software engineer to develop a model, it's quite an orthogonal skill, you need a solid grasp on mathematics and especially statistics.
It's not easy, but there are capable developers that are proficient in data science and it may be cost effective to hire one such (high cost) programmer than one (average cost) data-scientist and another (average cost) programmer.
Re: Demand and Salaries for Data Scientists Continue to Climb
#37Earlier quoted context omitted.
And software architect
That's a fun job, though. You can spend your entire tenure explaining to people that just because something starts and serves up a web page, it's not a good idea to run 30 year old software in Production... eventually you get to the point where you can only hire Senior Software Engineers to take care of our software and then it becomes a fucking priority to unfuck your stack because your payroll costs are the most ex…
> because your payroll costs are the most expensive line item
Payroll costs are always the most expensive item. And they should be.
Re: Demand and Salaries for Data Scientists Continue to Climb
#38Earlier quoted context omitted.
It's relevant for software engineers who read the title and consider going into data science instead.
Except most software engineers aren't qualified to go into data science.
What exactly are the qualifications? I would have thought a serious, sustained study of statistics--starting with a strong base knowledge of the mathematics of probability and building from there. But based on the resumes I've seen that doesn't seem to be the common opinion.
Re: Demand and Salaries for Data Scientists Continue to Climb
#39Earlier quoted context omitted.
"data engineer" is often considered a lower prestige title than data scientist. "Data scientist" is a title recently thrown around a lot for positions that used to be called "data analyst", with no strong ML or SWE ability required. Amazon's title for scientists with strong ML engineering ability is called "Applied Scientist" and it's paid significantly higher than SWE
You're claiming to know amazon internal except you're also using SWE, not SDE, the standard name for software devs there. Also amazon seems to hire very few Applied Scientists and thus is likely cherry picking for this role. The one I work near is an industry thought leader at Principal Applied Scientist. They'd be a leading researcher if they were in academia.
Software engineers are given the SDE title at Amazon but I just used SWE as the more general "software engineer" acronym.
Re: Demand and Salaries for Data Scientists Continue to Climb
#40Earlier quoted context omitted.
Data Engineer role is about building big data/streaming pipelines for data and often DevOps aspects of keeping such pipeline deployed and online. A boring, dead-end job. Avoid. Make yourself both ML/DL master and SWEng and you'll be doing extremely well.
You know that's usually the hard part of ML projects, right? It may be boring, but it also tends to be the less least replaceable component.
He's right about how data pipeline work is regarded by most ML scientists. It often ends up being extremely hard work and is regarded by others as useless grunt work. There is no big reward, constant overtime due to unexpected issues and lots of stress.