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  • - My advice to an aspiring data scientist is to be curious,

  • extremely argumentative,

  • judgmental.

  • Curiosity is absolutely must.

  • If you're not curious,

  • you would not know what to do with the data.

  • Judgmental because if you do not have

  • preconceived notions about things,

  • you wouldn't know where to begin.

  • Argumentative because if you can argue

  • then you can plead a case,

  • at least you can start somewhere.

  • And then you learn from data

  • and then you modify your assumptions and hypothesis,

  • and your data would help you learn.

  • And you may start at the wrong point,

  • you may say that I thought I believed this

  • but now with data I know this,

  • so this allows you a learning process.

  • So curiosity, being able to take a position,

  • strong position, and then moving forward with it.

  • The other thing that a data scientist would need is

  • some comfort and flexibility with analytics platforms.

  • Some software, some computing platform but that's secondary.

  • The most important thing is curiosity

  • and the ability to take positions.

  • Once you have done that,

  • once you've analyzed, then you've got some answers.

  • And that's the last thing that a data scientist needs

  • and that is the ability to tell a story.

  • That once you have your analytics,

  • once you have your tabulations,

  • now you should be able to tell a great story from it.

  • Because if you don't tell a great story from it,

  • your findings will remain hidden,

  • it will remain buried, nobody would know,

  • but your rise to prominence is pretty much relying on your

  • ability to tell great stories.

  • A starting point would be to see

  • what is your competitive advantage?

  • Do you want to be a data scientist in any field

  • or a specific field because

  • let's say you want to be a data scientist and work for an

  • IT firm or a web-based or internet-based firm.

  • Then you need a different set of skills.

  • And if you want to be a data scientist for

  • let's say in the health industry,

  • then you need different sets of skills.

  • So figure out first what your interest is

  • and what is your competitive advantage.

  • Your competitive advantage is not

  • necessarily going to be your analytical skills.

  • Your competitive advantage is your understanding of

  • some aspect of life where you exceed

  • beyond others in understanding that.

  • Maybe it's film, maybe it's retail,

  • maybe it's health, maybe it's computers.

  • Once you have figured out where your expertise lies,

  • then you start acquiring analytical skills,

  • what platforms to learn.

  • And those platforms, those tools would be specific to the

  • industry that you're interested in.

  • And then once you have got some proficiency in the tools,

  • the next thing would be to apply your skills to

  • real problems and then tell rest of the world

  • what you can do with it.

- My advice to an aspiring data scientist is to be curious,

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B1 中級

新米データサイエンティストへのアドバイス【データサイエンス101 (Any advice for new data scientist [Data Science 101])

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    陳賢原 に公開 2021 年 01 月 14 日
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