Author sounds like a young person who feels like he's a god among men just for the fact that he's implemented the algortihms and understands the math and engineering behind the libraries most DS's just pip install.
Which is weird coming from a generation of devs, where actually doing this work yourself was the norm.
As for DS, from what little I've experienced from the field, he sounds right. Most people come in without a mathematically rigorous education, they talk fancy, but what they end up doing is pulling in dependencies from a pre-written library and using those without understanding the theory behind them.
They also ignore the fact that 99% of the value in data science is created by taking good data, understanding the domain, in which case fancy algorithms are unnecessary. And the acquisition of said things needs good data engineering, not data science.
But more often than not, the credit and prestige goes to folks who pull in fancy ML algorithms and run extensive experiments and build massive ML pipelines, feeding in truckloads of tangentially relevant data.
I almost laughed out loud when he said he started working as a data scientist in 2019. Five years is not a very long time. And he claims he already had identified the entire field as full of fraud in the first two years of that!
I agree with a lot of the article's points, but the author took a serious credibility hit with me after asserting that two years of from-scratch experience is enough time to evaluate an entire subfield of computer science.
You start quite condescending but then basically acknowledge what the author is saying. Most DS's, even "from your generation" probably don't write their own tools. I bet you are even guilty of this too. No need to do some implicit grandstanding.
Please don't take HN threads into nationalistic flamewar. I know you didn't intend to but it's what this kind of internet comment leads to (in the general case), and we don't want that here.
In fact, since your comment is a putdown both of a nationality and of the community, it might be good to quote this from https://news.ycombinator.com/newsguidelines.html: "Please don't sneer, including at the rest of the community."
You realize that this comment was a very minor tease?
This community is so Us-centric that the pro-US-on-anything bias drives basically every voting trend, and the issue is just teasing how Americans don’t understand other nationalities’ humor and cultural nuances?
Unfortunately people tend to underestimate their own provocations by 10x or more. Even when we get full out flamewars the instigator inevitably says things like 'but I was only mildly teasing' or what have you. In any case, what matters is effects, not intent, and that's what we have to moderate by (https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...). The effects of snark, flamebait, and so on are predictable, so commenters are responsible for avoiding them.
Not sure about tall-poppy syndrome, but I think it's somewhat justified (this could be argued though) that success most often doesn't look like what we think it should look like.
In most people's minds success should come from a combination of talent and hard work. We think people who work hard and come up with good ideas should become successful.
But usually working 'within the system' limits your ability to be succesful. If you save the day at your current job, you might get a 20% raise if you're lucky. If you are mediocre but change jobs often, you will probably beat that.
In software, getting a high paying job usually hinges on your ability to get someone willing to pay you a lot of money.
I'm sure there are people who are getting paid 10x more or less for doing work that is fundamentally the same, just with different presentation.
For example I know a guy who's a mediocre PHP dev, but managed to snag a couple of high paying clients, and got into OE over covid, and brings in a ton of money, despite the fact that somehow he still doesn't seem to be working that hard.
Does he deserve that money? Is he someone we should look up to? I don't wanna say no, but I also don't wanna say yes.
> We think people who work hard and come up with good ideas should become successful.
I think that's some sort of platonic ideal that hasn't really been all that true for a long time, though. What brings success is coming up with valuable[0] ideas, and then executing well on them. There are many ideas that are good that are unfortunately not so valuable. And there are many people who work hard but just aren't all that talented or effective or productive, and their work ends up not amounting to much.
> Does [someone who doesn't work that hard but has high income] deserve that money? Is he someone we should look up to? I don't wanna say no, but I also don't wanna say yes.
Maybe we should step back and consider that this is the wrong question. "Looking up to" someone is an emotional thing; IMO we should only look up to people for intangible "virtuous" reasons, not because e.g. they've managed to make a bunch of money. Look up to people because they are honest, have integrity, are kind, and help people.
"This guy makes a lot of money despite not working very hard" should be viewed dispassionately. Evaluate the work itself, and the representation and selling of that work. If it's done with integrity, the product of the work is as promised, and no one is harmed, then it may be worth emulating.
I personally think that the social conditioning we've all gotten that suggests that hard work is good and virtuous is garbage, and is an attitude and message that has acted as a tool of oppressors. I hesitate to repeat the "work smarter, not harder" buzz-phrase, but I think there's a lot of truth there.
[0] I don't even necessarily mean "valuable" in the monetary sense, though that too-often is a big driver.
I have Australian friends and they are not like this.
Sorry but, being Australian doesn't get you a free pass to banter everywhere and still expect to be taken seriously. Let alone spill self-diagnosed superiority in form of text.
He grew up in Penang, moved to Australia in 2013 according to his blog.
I'm not a fan of the "I'll break your neck" theme. He doesn't want people talking about AI but his own business website says he'll talk to you about AI in exchange for money.
Does he want to be Louis CK Live at the Beacon Theater AND a data scientist consultant? I don't think it's possible to be both.
Only a small portion of HN users are in Silicon Valley. Last time I looked at the numbers (a few years ago) it was around 10%. About 50% were in the US overall, a third or so in Europe, and so on.
Which is weird coming from a generation of devs, where actually doing this work yourself was the norm.
As for DS, from what little I've experienced from the field, he sounds right. Most people come in without a mathematically rigorous education, they talk fancy, but what they end up doing is pulling in dependencies from a pre-written library and using those without understanding the theory behind them.
They also ignore the fact that 99% of the value in data science is created by taking good data, understanding the domain, in which case fancy algorithms are unnecessary. And the acquisition of said things needs good data engineering, not data science.
But more often than not, the credit and prestige goes to folks who pull in fancy ML algorithms and run extensive experiments and build massive ML pipelines, feeding in truckloads of tangentially relevant data.