the fact is all the knowledge that a data scientist has should already be discoverable by any decent programmer. Basically college level statistics is required to be a data scientist. If your engineer cant handle that I hope they are more frontend than backend.

Data science does have particular algorithms and analysis graphs that are unique to the field but the underlying math is set theory and statistics.

"Data scientist" is a fancy title for "smart math guy". But math without application gets you no where. You need someone to put it into the machine.

Depends. If it’s a spam classifier, yeah I agree. If it’s estimating causal models for some type of economic analysis it will be harder for a self taught SDE to compete with someone with academic research experience dealing with messier social sciencey economic data.

Actually spam classifiers are not easy at all.

First, the data is very unbalanced.

Second, you would need to retrain the model often. So you would need to understand statistical methods for comparing text level/word level distributions. This is not a college-level stat.

Third, you would need deep knowledge in NLP, feature engineering and algorithm selection.

I didn't say it's easy, I said it's something more amenable to an SDE self-learning.

I think the point is that the person with academic research experience dealing with messier social sciencey economic data would/should have basic junior SDE level programming skill.

If not, say that his research is conducted in excel, I'd still rather have the former.

Yeah. I agree with you, as I have both the academic research skills and the SDE level programming skills as a DS (by only doing a masters I was able to get out of academia earlier and develop some SDE skills instead of writing a dissertation). But every once in a while we hire someone who is in their early 30s and just finished academia, and despite sucking at engineering, can blow everyone away scientifically. I think a well crafted 2-pizza team can support 1 or 2 of those people.

> 2-pizza team

Unrelated, but since you spoke of this, I just want to tell you whoever came up with this term severely underestimated our teams appetite.

its the game that is successful not the software. This game could be written many different ways. Players dont care. Now if there is a particular pain point or glitch in the game and it can be shown that its the style of code that allowed for this to happen. That better organized code would have mitigated this bug then that is important to investigate.

But trying to figure out what a successful game is by its source code is like trying to find what makes a painting good analyzing the chemicals used to make the pigments.