Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Cargo cult data science

blog.richardweiss.org

Post reply on HN
Print view View original

21–30 of 42 posts

Re: Cargo cult data science

#21

Post by gaius »

gipp wrote: post #18
gaius wrote: post #16

Earlier quoted context omitted.

It's quite a famous quote, I think it was the chief data scientist at LinkedIn who coined it originally. There is real value in being a "statistical programmer" but that value can't presently be seen past the smoke and mirrors.

I think you're thinking of Josh Wills, Cloudera at the time, now Slack: https://twitter.com/josh_wills/status/198093512149958656?lan... > Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician. A lot less braggadocious than what you're suggesting, it's just talking about it as a jack-of-all-trades type of job.

"Average" would have been more realistic, and as I say there is value in the role. If DS keeps promising and failing to deliver miracles, it will never be more than a fad. Someone with a job title of "applied mathematician" already does was DS claims to do... the title of "statistical programmer" or "statistical engineer" is a better one, than "data scientist".

Re: Cargo cult data science

#22

Post by peacetreefrog »

In my experience, there're (at least) two ways of using data in an organization:

1. Top down. Where you start with a problem/decision, and use data to inform it. "What phone plan should we offer our customers?" per the article is topdown, and data science can help inform the answer.

2. Bottom up. Where you start with a bunch of data, and try to brainstorm, "OK what cool things can we do with this?". I worked for an IOT company that collected a bunch of sensor data and we'd run into this all the time. We'd take our best shot and report back to clients, who'd say, "Cool, but what do I do with this?". Not saying you can NEVER come up with something useful, but it's a lot harder.

Re: Cargo cult data science

#23

Post by padthai »

hkon wrote: post #19
soVeryTired wrote: post #13

Earlier quoted context omitted.

"Experiments" doesn't have four Es. Unless it's meant to be some sort of pun on "experience".

Yes, I was just having a bit of fun. People cannot even point out spelling errors without hedging their statements. (right?)

I was unsure because the blog is two years old. Two years with a typo in the title is quite a bit.

Maybe it was some kind of subtle joke that I do not get.

Re: Cargo cult data science

#24

Post by [deleted] »

Bartweiss wrote: post #17
gipp wrote: post #14

When the author says: > However, that assumes that someone presenting an analytical presentation will be viewed more favourably than someone presenting something softer. Basically, I had assumed a data-driven culture exists, when in reality businesses are struggling to create that culture in the first place. I think this understanding of the situation is in itself part of the problem. It assumes that someone coming i…

> An organization which _always_ values data-driven decision making over expertise-driven decision making is always going to fall prey to this myopia. This is a huge and under-appreciated concern. It's disturbing how often success is measured by optimizing a single metric, and how resistant people can be to recognizing issues with this approach. A goal like "improve clickthrough rates" is easy to measure, but without…

[deleted]

Re: Cargo cult data science

#25

Post by conjectures »

gipp wrote: post #14

When the author says: > However, that assumes that someone presenting an analytical presentation will be viewed more favourably than someone presenting something softer. Basically, I had assumed a data-driven culture exists, when in reality businesses are struggling to create that culture in the first place. I think this understanding of the situation is in itself part of the problem. It assumes that someone coming i…

On that point, Superforecasting by Tetlock is an excellent book on softer analysis, which will make perfect sense to quant readers.

Re: Cargo cult data science

#26

Post by eanzenberg »

gaius wrote: post #3

However, that assumes that someone presenting an analytical presentation will be viewed more favourably Well, it certainly isn't helped by data scientists claiming to be better than ANY programmer and ANY statistician. Who could possibly live up to their own hype? A DS and ML winter will follow just as it did for AI.

Wat? I don't think any DS is claiming to be better than any programmer and statistician. I think the anecdote you refer to is, a DS is better at programming than a statistician and is better at statistics than a programmer. This viewpoint holds up in my experience.

Re: Cargo cult data science

#27

Post by gipp »

conjectures wrote: post #25
gipp wrote: post #14

When the author says: > However, that assumes that someone presenting an analytical presentation will be viewed more favourably than someone presenting something softer. Basically, I had assumed a data-driven culture exists, when in reality businesses are struggling to create that culture in the first place. I think this understanding of the situation is in itself part of the problem. It assumes that someone coming i…

On that point, Superforecasting by Tetlock is an excellent book on softer analysis, which will make perfect sense to quant readers.

Oh, not familiar, looks good! Ordered.

Re: Cargo cult data science

#28

Post by gipp »

gaius wrote: post #21
gipp wrote: post #18

Earlier quoted context omitted.

I think you're thinking of Josh Wills, Cloudera at the time, now Slack: https://twitter.com/josh_wills/status/198093512149958656?lan... > Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician. A lot less braggadocious than what you're suggesting, it's just talking about it as a jack-of-all-trades type of job.

"Average" would have been more realistic, and as I say there is value in the role. If DS keeps promising and failing to deliver miracles, it will never be more than a fad. Someone with a job title of "applied mathematician" already does was DS claims to do... the title of "statistical programmer" or "statistical engineer" is a better one, than "data scientist".

Yeah, I agree completely, I just don't think that the hype of the role is coming from practitioners.

I know this isn't really your point, but I've met Josh Wills, for example, and listened to many of his talks. I don't think I've met a more realistic guy (among actual practitioners) when it comes to the expectations and reality of doing corporate data science. The hype, I'd say, is just an emergent phenomenon of the tech reporting cycle. Nobody's out there _trying_ to inflate expectations, except a few consultants and "thought leaders" maybe.

Re: Cargo cult data science

#30

Post by dmix »

gipp wrote: post #14

When the author says: > However, that assumes that someone presenting an analytical presentation will be viewed more favourably than someone presenting something softer. Basically, I had assumed a data-driven culture exists, when in reality businesses are struggling to create that culture in the first place. I think this understanding of the situation is in itself part of the problem. It assumes that someone coming i…

This is an interesting point.

I'm curious if one of the 'myths' of a data driven company is that you can instantly begin making decisions fed by 'real-time data' and learn after-the-fact from feedback loops. But for many legacy businesses the data pipeline for their important KPIs still moves slowly.

And then the data that does come in quickly becomes over-valued because everyone was sold the idea of instant gratification. So there is pressure to react to things quickly like meaningless web traffic metrics or local sales data - which may fluctuate heavily on a daily basis - instead of waiting for relevant patterns to emerge over longer periods.

Statistical significance and error rates are then overlooked in the name of a cargo cult data culture.

This is why business books can be dangerous or even destructive, as business advice from one person's experience is sold as generic design patterns that apply to every business - which isn't the case. This is why understanding the business inside-and-out is the most important attribute, then having MBA-esque skills/toolset is useful second. So you take the reality of the business into full consideration and apply tools to it, rather than seek out tools and pigeonhole your business into them.

Post reply on HN