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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

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.

natalyarostova 7y ago
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.
- deleted 7y ago
  [deleted]
- Aperocky 7y ago
  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.
  - natalyarostova 7y ago
    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.
    - Aperocky 7y ago
      > 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.
- streetcat1 7y ago
  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.
  - natalyarostova 7y ago
    I didn't say it's easy, I said it's something more amenable to an SDE self-learning.

natalyarostova 7y ago

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.

deleted 7y ago
[deleted]
Aperocky 7y ago
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.
- natalyarostova 7y ago
  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.
  - Aperocky 7y ago
    > 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.
streetcat1 7y ago
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.
- natalyarostova 7y ago
  I didn't say it's easy, I said it's something more amenable to an SDE self-learning.