Metadata
- URL:: https://ryxcommar.com/2022/11/27/goodbye-data-science/
- Author:: W.D
- Publisher:: ryxcommar.com
- Published Date:: 2022-11-27
- Tags::
Highlights
- work was only often as good as the weakest link in that chain.
- Managers will say they want to make data-driven decisions, but they really want decision-driven data.
- The median data scientist is horrible at coding and engineering in general.
- It seems like the main career growth data scientists subject themselves to is learning the API of some gradient boosting tool or consuming superficial + shallow + irrelevant knowledge.
- For the life of me I cannot see how reading a blog post that has sentences in it such as “DALL-E is a diffusion model with billions of parameters” would ever be relevant to my work.
Metadata
- Author: W.D.
- Full Title:: Goodbye, Data Science
- Category:: 🗞️Articles
- Document Tags:: Data culture,
- URL:: https://ryxcommar.com/2022/11/27/goodbye-data-science/
- Finished date:: 2023-09-21
Highlights
The work is downstream of engineering, product, and office politics, meaning the work was only often as good as the weakest link in that chain. (View Highlight)
Nobody knew or even cared what the difference was between good and bad data science work. Meaning you could absolutely suck (View Highlight)
When the work’s value-add exceeded the labor costs, it was often personally unfulfilling (e.g. tuning a parameter (View Highlight)
Companies all over were consistently pursuing things that could be reasoned about a priori as being insane ideas (View Highlight)
Managers will say they want to make data-driven decisions, but they really want decision-driven data (View Highlight)
The median data scientist is horrible at coding and engineering in general. (View Highlight)
Personally, I’ve benefited a ton from reading the first couple chapters out of advanced textbooks (while ignoring the last 75% of the textbook), and refreshing on embarrassingly pedestrian math knowledge like “how do logarithms work.” (View Highlight)
I admit this is perhaps a strange way to live one’s life, but it worked for me: after having gauged my eyes out on linear regression and basic math, it’s shockingly apparent to me how much people merely pretend to understand this stuff, and how much ostensible interest in more advanced topics is pure sophistry. (View Highlight)
One of the main sins of “data scientist” jobs is that it expects far too much from people. (View Highlight)