July 15

Miscommunication Etude #2

Manager: I have told you to start doing research on Z last month.

Data Scientist: Yes, you did.

Manager: It was your only priority that you have been working on, hasn’t it?

Data Scientist: Yes, it has.

Manager: When will it be ready for deployment?

Data Scientist: In about 2 months.

Manager: But last month you also told me about 2 months. So there should only be 1 month left, shouldn’t it?

Data Scientist: Not quite, because you have asked me to start doing research on it, not to prepare it for deployment.

Manager: And what have you done?

Data Scientist: I have come up with many ideas and created numerous improvements. Some code is now in a library that might be useful in the future. Also, I have evaluated a few algorithms from a recent scientific paper.

Manager: Have you at least decided which approach you will use?

Data Scientist: No, you have not asked me to think about deciding. 

Manager: Well, why do you think we have this project?

Data Scientist: Because we want to build and deploy a model.

Manager: And why do we want to build and deploy a model?

Data Scientist: Because we are a data-driven company. That is what we do.

Manager: Don’t you think it has to do anything with customers or profit?

Data Scientist: I could anticipate this one was coming… Sometimes, yes. But the best research is only created in a pure environment, where there is no pressure to worry about users or profit. Just like popular music is inferior to classical music, many companies are mediocre because they are trying to be “practical”. Or ask any Nobel prize winner: rushing is never a way to greatness. 

Manager: Point taken. I understand that there are multi-year research projects at Microsoft Research or at MIT, and that those are very important for humanity. But don’t you think that sometimes there can be a tradeoff between quality and timely results that we have to deliver to stakeholders?

Data Scientist: Is it your personal opinion, or do you think the CEO would also agree with your assessment?

Manager: I am pretty sure that the CEO would also insist on timely deliverables.

Data Scientist: That’s unfortunate! I can certainly put in some extra hours when there is a deadline. My concern is, this company does not seem to have the right values. If the focus is on short-term results instead of investing in quality tech and R&D, this means nothing good will ever come out of what I am doing here. I should probably look for another job somewhere better, where my profession is actually valued.


data science, soft skills

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