Comment by nmrcq | Hacker News Reader

Comment by nmrcq | Hacker News Reader

With all due to respect to the author of the site, mastering all the materials in the machine learning or data scientist path will make you a solid 'applied' machine learning/statistical learning practitioner, but not an expert, and definitely not a research candidate.

We should be careful with how we guard our scale of semantic meaning - if somebody with an undergrad understanding of statistics (frequentist statistics only in this map) can be called an Expert in a statistical/mathematical field, what do we even call somebody with all the same applied software engineering & exploratory analysis, and business experience, but also a PhD in theoretical topics (math, stats, etc)? A 'super expert'? What do we call Francis Chollet, or LeCun, or anybody else? What's the differentiation between an expert from the roadmap and the team of individuals deploying GPT-3 into Google Assistant? Are they the same?

As a hiring manager and team lead for a large fintech firm in London, I would happily see an individual who had really mastered the above path(s) as a strong candidate for an intermediate or upper junior role in applied data science/machine learning. But ... it's not enough to be a senior, and certainly not an expert. Just my two cents.

Using a PhD as a gateway into applied ML is so horrifically misguided I hardly know where to even begin debunking it.

PhDs are one especially crappy way to prove you have the intellectual chops to engage with ML. There are far more direct, practical, and expedient alternative paths to get there.

Importantly, the number of people who were perfectly capable of doing a PhD but chose not to (because, frankly, it's a very bad deal) vastly dwarfs the number of people who stuck around in academia and obtained one. Additionally, my observation at several major tech companies is that PhDs have a bent of mind that is roughly orthogonal to the pursuit of real business value.

Yikes! This doesn't really come across as a nice comment (bent minds???). There are good concrete reasons to pursue a PhD (ignoring soft reasons like pure interest): wanting a research career is one - it's pretty difficult to get hired as a scientist without a PhD. Also, historical evidence doesn't really support your claim that R&D is orthogonal to business value. Sure, pure science is often independent from $$$ (despite plenty of examples of producing real value), but applied R&D is oftentimes parallel to value generation. if R&D in general is useless, why do top tech companies spend big money on research groups?

Getting a PhD is a fine deal if you have good reasons.

I explicitly caveated my statement with "Using a PhD as a gateway into applied ML" for a reason. The vast majority of people going into applied ML are not pioneering new methods. They're using ML as a tool to support business objectives. This is the group I'm talking about.

The phrase "bent of mind" roughly implies "the way someone thinks". Its usage is declining I suppose but there's nothing connotatively nefarious there.

Yeah - I looked it up. Thanks!

Bent of mind is a phrase that means proclivity or predisposition, and PhDs are famously arduous.

Expertise is relative. Having compiled a few kernels in my life I wouldn't consider myself an operating systems expert, but to a career plumber, I am. Heck, a friend of mine is a PhD in physics, operates a particle accelerator for work, and to him I'm an operating systems expert despite my protests to the contrary.

You're an expert if other experts say so. The opinions of clueless folk are just random noise.

Just because the man who can see is king among blind men doesn't mean they're qualified to call him visionary.

> What do we call Francis Chollet, or LeCun, or anybody else?

Ehhh, French? I like Chollet(many people dont) but he is not in the same league of Yan LeCun at all.

It seems both the author and you have a naive view of expertise in academia.

Agree 100% with you but would add that from the perspective of a lot of business people, the bar for expert is actually pretty low and however far over it you are, they dont actually get any more out or you because they don't know what to do with you. What a lot of businesses want is someone they can call an expert but that still operates within the realm and understanding of a non specialist manager.

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