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Ask HN: What's the state of the job market in data science and machine learning?

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Re: Ask HN: What's the state of the job market in data science and machine learning?

#41

Post by plafl »

runT1ME wrote: post #13
hardtke wrote: post #11

I hire machine learning engineers and data scientists. In my opinion there is a great shortage of truly qualified machine learning engineers. A lot of people are entering the market with a general knowledge of machine learning tools. These people should be considered analysts or product data scientists. When it comes to people that can build machine learning systems that work at scale, they are very rarely available…

> The key difference is whether the candidate truly understands the mathematical and statistical basis of machine learning Can you elaborate on this, and at what level? Are you talking about a PhD level of understanding of cutting edge mathematics, or do you mean understand the basics, or somewhere in between?

I usually ask about what the candidate has worked on. Or maybe the topic of their PhD thesis. I prefer that people explain to me what they know instead of having a list of questions about what I know.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#42

Post by user5994461 »

hellogoodbyeeee wrote: post #34
rm999 wrote: post #23

Speaking for NYC, but I imagine silicon valley is similar. The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it. The second group has gotten extremely crowded, esp…

Do you have advice for someone in the second camp? I have a master's in econ and I'm comfortable in R but I don't have good development skills. I'm wondering if I need to give up on data science jobs for a bit and try and find an entry level software development job

Take whatever job you can... as far as it's related to the kind of things you want to do.

Forget about the big companies that everyone knows, forget about the high pay that appear in the newspapers. It's not real, it's not for you.

Get an entry or junior level position and get experience. There are many unknown places that will take people only because they're cheap. That's where everyone started.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#43

Post by freyr »

platz wrote: post #2

I considered a graduate program in data science, but compared to average programmer salaries, it doesn't seem like data science pays all that much (excluding data science jobs for PHD's in silicon valley). It's more interesting that programming, but seems like a much tighter market with no discernible demand driving salaries up.

Interesting. I have a statistics/data science background, but personally I find programming much more satisfying.

Programming is a tool to create and synthesize. It leads to new products, companies, and solutions. Data science is analysis, not synthesis. You collect data, you interpret it, you move on to other data. Nothing gets created, which for me, is a deal breaker for job satisfaction.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#44

Post by omginternets »

shas3 wrote: post #36
rm999 wrote: post #23

Speaking for NYC, but I imagine silicon valley is similar. The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it. The second group has gotten extremely crowded, esp…

Frankly, MOOC-type machine learning- being able to do plain vanilla logistic regression or black-box deep learning techniques is not enough to get a job. This knowledge and experience has to be paired with one or more strengths: excellence in programming, grad-level math/stat/numerical skills/theoretical machine learning, domain specific expertise or experience (e.g. vision, audio, natural language, networks, geophys…

> vision

Could you elaborate on which elements of vision science are relevant? Do you have any examples of what these people end up working on?

Re: Ask HN: What's the state of the job market in data science and machine learning?

#45

Post by user5994461 »

rafinha wrote: post #38
rm999 wrote: post #23

Speaking for NYC, but I imagine silicon valley is similar. The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it. The second group has gotten extremely crowded, esp…

Isn't it 2 profiles of engineers? Those who make production code and those who work in prototypes? One thing is to understand why your model isn't converging, another is how to scale it up...

2 profiles:

- Research departments that make prototypes that are consistently abandoned and never get any real world usage.

- Actual companies that make prototypes for real business cases that are then shipped to production, maintained and improved as they bring in $$$.

The first experience is of limited value to the world of real business.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#46

Post by hellogoodbyeeee »

user5994461 wrote: post #42
hellogoodbyeeee wrote: post #34

Earlier quoted context omitted.

Do you have advice for someone in the second camp? I have a master's in econ and I'm comfortable in R but I don't have good development skills. I'm wondering if I need to give up on data science jobs for a bit and try and find an entry level software development job

Take whatever job you can... as far as it's related to the kind of things you want to do. Forget about the big companies that everyone knows, forget about the high pay that appear in the newspapers. It's not real, it's not for you. Get an entry or junior level position and get experience. There are many unknown places that will take people only because they're cheap. That's where everyone started.

Thanks for your comment. It has eased some of the anxiety caused by reading through this thread. My current job fits your description. I currently have an analyst role and I spend maybe 25% of my time building predictive models in R. I just haven't had any success finding a role that ups that percentage (and the pay). I know I need to be more patient, but it is difficult.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#47

Post by elastic_church »

rafinha wrote: post #38
rm999 wrote: post #23

Speaking for NYC, but I imagine silicon valley is similar. The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it. The second group has gotten extremely crowded, esp…

Isn't it 2 profiles of engineers? Those who make production code and those who work in prototypes? One thing is to understand why your model isn't converging, another is how to scale it up...

the data science people I've worked with in multiple VC backed companies were not engineers at all. They were either "data scientists" or had engineer tacked on to the name.

I'm continually exposed to new kinds of software engineering roles I never heard of at tech companies. (fwiw software engineer is sometimes still considered an inflated title.)

Re: Ask HN: What's the state of the job market in data science and machine learning?

#48

Post by shas3 »

omginternets wrote: post #44
shas3 wrote: post #36

Earlier quoted context omitted.

Frankly, MOOC-type machine learning- being able to do plain vanilla logistic regression or black-box deep learning techniques is not enough to get a job. This knowledge and experience has to be paired with one or more strengths: excellence in programming, grad-level math/stat/numerical skills/theoretical machine learning, domain specific expertise or experience (e.g. vision, audio, natural language, networks, geophys…

> vision Could you elaborate on which elements of vision science are relevant? Do you have any examples of what these people end up working on?

I loosely used the term to refer to computer vision, which overlaps a bit with vision science (especially color, perception, etc.). But yeah, computer vision.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#49

Post by plafl »

I can speak for Spain, although I sometimes get calls from other European countries. Relative to the pathetic Spanish work market data science/machine learning is doing great. I think right now there is too much hype, which is going to stay for a few years. After that I suppose it won't be a hot thing but I don't think it's going to disappear. I hope I'm mistaken and we are really seeing some AI revolution, but after all my job is putting the trust on the data, and past data says fads come and go. If that happens I will keep with me the math, the statistics, any development skills I can learn meanwhile and of course the challenge of someday achieving true AI.

Re: Ask HN: What's the state of the job market in data science and machine learning?

#50

Post by kafkaesq »

wjn0 wrote: post #33
curiousgal wrote: post #16

Earlier quoted context omitted.

>or simply because we can abstract a lot of this away (ex: TensorFlow). That would work up to the point a better abstraction tool/framework comes along. I'd never try to build a career on a single framework, because frameworks come and go.

Building a career around a framework is never a good idea. If you know your shit, it shouldn't matter what framework you're using. Theano and TF, for example, both make similar abstractions: graphs and numerical functions on top of the same matrix library, even. I would suspect someone could move between the two fairly easily. The problem is that a programmer can use TF/Theano/etc.'s built-in gradient descent functio…

If you know your shit, it shouldn't matter what framework you're using.

And yet, what is the incessant drumbeat of most job ads, these days - even in data science?

That's right: "N years in framework X"

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