1.3.2.Careers and Recruiting in Data Science - sj50179/IBM-Data-Science-Professional-Certificate GitHub Wiki

How Can Someone Become a Data Scientist?

If you're coming into a data science team, I think the first skills you need is you need to know how to program, at least have some computational thinking, so having taken a programming course, you need to know some algebra(대수학), at least up to analytics(해석학), geometry(기하학), and hopefully some calculus(미적분학), some basic probability(확률), some basic statistics(통계); I mean really have to understand the difference and different statistical distributions, and database. I mean, one of the easiest places to start is relational databases(관계형 데이터베이스), which stores lots and lots of our data so people can first walk before they can run by at least understanding about computers and databases and how we store things and if you understand relational databases nowadays you can still, just with that understanding, use big data clusters as if they were just a big relational database. You don't have to really have understand the whole MapReduce programming model. But then, as you go further up in the field, then you have to know a lot of computer science theory and statistics, it's really, and probability, it's really the intersection of them that the high end data scientists, the PhD data scientists work with.

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Recruiting for Data Science

"I would say if I'm looking for someone, if I have to put together a data science team, I would first look for curiosity. Is that person curious about things not just for data science but anything like, are they curious about why this room is painted a certain way, why do the bookshelves have books, and what kinds of books? They have to have a certain degree of curiosity about everything that is in their vision, that they look at. The second thing is do they have a sense of humor because, you see, you have to have a lighthearted about it. If someone is too serious about it, they probably would take it too seriously, and would not be able to look at the lighter elements. The third thing I think, and I think the last thing that I would look for if I had to have a hierarchy, the last thing I would look for are technical skills. I would go through the social skills, curiosity, and sense of humor. The ability to tell a story. The ability to know that there is a story there. And then once all is there then I would say, well, can you do the technical side of it? And if there is some hope or some sign of some technical skills, I would take them because I can train them in whatever skills they need. But I cannot teach curiosity. I cannot teach storytelling. I cannot certainly, instill sense of humor in anyone."

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Careers in Data Science

What motivates someone going into a data science? For one thing, data science applies to almost any discipline. So if you have the aptitude and desire to work with data, enjoy coding, have no problem learning math and statistics, and you are a good storyteller, then you can certainly enter a data science field and excel. For most people, this means acquiring additional tools and skills and continuously learning about new tools and techniques in the field.

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Lesson Summary

In this lesson, I have learned:

• Data Scientists need programming, mathematics, and database skills, many of which can be gained through self-learning. 데이터 과학자는 프로그래밍, 수학, 데이터베이스 기술을 필요로 하며, 그 중 많은 기술은 자가 학습을 통해 얻을 수 있다.

-Companies recruiting for a Data Science team need to understand the variety of different roles Data Scientists can play, and look for soft skills like storytelling and relationship building as well as technical skills. 데이터 사이언스 팀을 모집하는 기업은 데이터 사이언티스트가 할 수 있는 다양한 역할을 이해하고, 기술력뿐만 아니라 스토리텔링, 관계 구축과 같은 소프트 스킬을 찾아야 한다.

• High school students considering a career in Data Science should learn programming, math, databases, and, most importantly practice their skills. 데이터 사이언스에서의 직업을 고려하는 고등학생들은 프로그래밍, 수학, 데이터베이스, 그리고 가장 중요한 것은 그들의 기술을 연습해야 한다.