While I generally agree, I think there's a point in these 2 statements that can easily misinterpreted.
>It is likely that the Data Scientist role is in a long term decline...
Also
> Data science is in decline and vaguely defined
Reading this, you can think that "Data Science" jobs are decreasing. But I don't think that's true.
Let's just say that it's 2017 and I hire a team of 3 people with the job title of Data Scientist. One ends up focusing on the data side, one on modeling+analysis, and one on building the infrastructure. In 2023, I decide to change the job titles so one of them is now a Data engineer, one is now a Data Scientist, and one is now a ML Engineer to match what is happening in the job market.
It's still 3 jobs with 3 people doing the same thing. So the number of jobs aren't decreasing, but their titles are more specific. Overall, the number of "Data Science" jobs are still doing up.
Somebody will say "But that's exactly what the author said." But I think people who are new(ish) to this field might read it as "Data Science Jobs are decreasing." So I'm making this comment.
> skills such as data mining and visualisation are also out of favour.
Honestly, I just don't believe this. It's possible that as job descriptions are filled with different buzzwords, people just leave these out. For visualization it's also possible that there is a bigger focus on keywords of an established BI tool (e.g. PowerBI) instead of ad-hoc charts in matplotlib or ggplot. But some degree of data mining and visualization is useful, even to Data Engineers.
>With 10+ years in DS, I've always felt that best DS were always basically software engineers that knew math and were more interested in prototyping cool machine learning product than maintaining production infrastructure. Unfortunately this always accounted for a small fraction of DS I interacted with.
I've been a DS for 10+ years, and I feel the exact opposite. The worst "Data Scientists" I've worked with are all ex Software Engineers who seem to assume that business problems are really computation problems. So they find convenient ways to ignore the human aspects (e.g. trying to figure out why the data is a mess) and gravitate to using more complex algorithms and breaking down the problem to an achievable programming pipeline that runs in production, but the results are of low value. But it looks awesome on a resume.
Are you right or am I right about SWEs turned DS? I have no idea. But one quality that IMHO is important is the interest in actually looking at data and asking questions, which is much rarer than most people realize.
>Sadly, a new risk with "100% remote anywhere" culture.
I think this is a new risk when it comes to hiring engineers. This kind of fraud has been present outside of Engineering orgs for a long time.
I used to be a hiring manager in a well known company that was 100% onsite. This was on the business side, not IT/Engineering. We were looking for a BI person as a contract hire. Our HR org said they had a staffing agency they had worked with for years. The staffing agency sent us a bunch of resumes that were surprisingly similar, filled with every buzzword and feature (e.g. I made a bar chart) and obviously weren't written by the candidates. After throwing those out, there were a few that looked decent. We had some phone screens and then a single onsite interview, but concluded there was something fishy going on.
I confronted rep from the staffing agency with with this and their response was that typically somebody in a managerial position (at our company) picked a few resumes, had a phone call (not video, just phone) with them, then hired somebody based on the phone call. My team was the first one that had actually done more than that.
Who showed up on the first day, who actually did the work, I don't think anybody had any clue.
The non-technical managers didn't have the skillset to properly evaluate these candidates. So they saw the keywords and picked the person that sounded the best.
Engineers hopefully have the skillset to evaluate and interview other Engineers, so the fraud is different and more sophisticated now.
IMHO, if you're the type of manager who hires somebody like this and what you wanted done gets done, you've probably got bigger problems than a staffing agency scamming you. If you think it's rocket science to build a couple of charts in a BI tool and you're happy when the person you hired takes 6 months to build a couple of dashboards at $100/hr...good luck to you.
>but it does mean "hey, take a small team and do your own thing with less oversight and process overhead from higher-ups".
If you are interviewing for a "startup in a big company" job, one of the first questions you should ask is "how much oversight and process do we have from the larger company?" Make sure you ask a lot of questions about how decisions are made, who the product is being built for, how it is being sold, etc.
I've worked in two "startups" in two very different big companies. In both situations, the every major decision had to go through the larger org, which meant basically the whole thing was a waste. The only things that were approved were things the big company was already doing.
I'll provide a concrete example. I was involved in a product where our people had to work with the larger account execs of existing customers. The idea was the account execs could take the product to existing customers easily and grow very rapidly. What really happened was the account execs refused to put the product in front of customers unless it fit into the larger enterprise architecture strategy. They didn't need a startup - they needed a typical huge enterprise software team. So basically the product that got built was a completely half-baked POS that only looked good on slides. It was a market failure.
>Honestly, I don't understand why you would buy these when there are a lot of established professional audio companies offering better sound at a cheaper price.
Probably because most of these companies have been "upgrading" their headphones for years, but really just making tweaks and increasing the price. So much of it is just marketing.
I'm a former headphone addict who used to own a lot of expensive headphones. I saw the progression from when $300 was expensive (if you exclude the electrostatics), to suddenly $1k is the norm for a "High End" headphone. Then $1.5K, then $2000, etc.
I'm not planning to buy the Airpods Max, but I give kudos to Apple for finally stepping up with computational audio and doing more than just making minor tweaks and marketing the hell out of it. Apple might actually push the other manufacturers to get off their ass and do some actual innovation.
>Just it existing is a threat to the other providers.
In my area (a suburban area near Raleigh) it seemed like AT&T really got moving and deployed Fiber after Google put out the "coming soon" flyers. I hope Google keeps pushing forward, even if it's very slow. This will force other providers to improve.
It's amazing to me to learn that you can help other teams solve problems at Google.
Every big company I've worked for (none of them FAANG), helping another team is a recipe for disaster. You will get your hand slapped, punished, blamed, and basically make your life much worse. Each team is super insulated and tries their best to hide behind their management chain because of this.
It's great that you can feel bored and look for other problems to solve and not just teach yourself something new to stay challenged.
I was responding to your comment where you said "The behavior of slacker Googlers described here would have gotten them instantly fired in any European company."
There are a lot(!!) of European Multinationals, plenty of which are the typical slow moving bureaucratic mess where people who are good at meetings, presentations, and big talk end up moving up faster than people who just work hard.
In that sense, there are plenty of cities in the US where the software jobs are terrible, the pay is mediocre, and you work for employer who simply tries to squeeze as much from you as possible. That's one of the reasons there are so many people who migrate to parts of the US where they have more job options and better employers.
This is just my experience, but that isn't true at all. I work in the US for a huge European based Multinational with an HQ is Western Europe, Dev offices in Western and Eastern Europe, US, and Asia. There are plenty of devs all over the world who are slackers, but who know how to play the visibility and politics game well enough that they are perceived as high value.
I've worked for two other Multinationals and with consulting and partner firms in Europe and Asia. Some people are amazing and work really hard, and some know how to make themselves look good and get fancy positions (e.g. senior architect) where they slack off and keep themselves busy selling themselves by attending meetings. At one place I worked there was constant frustration that our European colleagues had no sense of urgency or motivation at all.
I think the point dhuyrv is making is that in many situations, you can take advantage of the fact that most people don't really know the difference between what you actually do and what you project to others. In many jobs (no matter where you are in the world), playing the game of selling yourself can do more for your career and salary than writing code.
>It is likely that the Data Scientist role is in a long term decline...
Also
> Data science is in decline and vaguely defined
Reading this, you can think that "Data Science" jobs are decreasing. But I don't think that's true.
Let's just say that it's 2017 and I hire a team of 3 people with the job title of Data Scientist. One ends up focusing on the data side, one on modeling+analysis, and one on building the infrastructure. In 2023, I decide to change the job titles so one of them is now a Data engineer, one is now a Data Scientist, and one is now a ML Engineer to match what is happening in the job market.
It's still 3 jobs with 3 people doing the same thing. So the number of jobs aren't decreasing, but their titles are more specific. Overall, the number of "Data Science" jobs are still doing up.
Somebody will say "But that's exactly what the author said." But I think people who are new(ish) to this field might read it as "Data Science Jobs are decreasing." So I'm making this comment.
> skills such as data mining and visualisation are also out of favour.
Honestly, I just don't believe this. It's possible that as job descriptions are filled with different buzzwords, people just leave these out. For visualization it's also possible that there is a bigger focus on keywords of an established BI tool (e.g. PowerBI) instead of ad-hoc charts in matplotlib or ggplot. But some degree of data mining and visualization is useful, even to Data Engineers.