What wonderful questions did the interviewer ask in those years?

Wonderful interview questions in those years

1, CCTV interviewer: Can you wear a three-point look?

Some time ago, we saw another excellent host, Yang Lan, on the stage of the finals of "Braving the Wind and Waves". She has the label of "intellectual beauty". Whether she is a guest host or a wonderful speech on behalf of "30+" women, people are all amazed: this is really a talkative person.

In fact, her "eloquence" and "eloquence" were well known when she first entered CCTV, which was related to her interview experience.

Yang Lan, who was still a rookie at that time, was stumped by the interviewer when applying for CCTV host. The other party asked an embarrassing question.

"Can I wear three-point clothes for the camera?"

However, we must know that the reform and opening up have not been long, and the domestic folk customs are still quite conservative. Such questions are likely to make the interviewer slam the door directly.

But Yang Lan didn't. She said quietly: "It depends on whether the current culture and morality are accepted. I remember a place abroad where they like naked baths for men and women. It is conservative to wear three-point clothes there, but in some places, women can't even show their hair to outsiders, and three-point clothes are definitely not allowed. "

This answer is both rational and rigorous, and it also shows the breadth of your knowledge. There is no doubt that Yang Lan was admitted.

In fact, the reason why the interviewer wants to come up with this seemingly embarrassing interview question is not to recruit an open or conservative person, but to recruit someone who is good at dealing with emergencies. This is a "stress test" for the interviewer.

2. If you are a data scientist of Tencent.

Tencent once had a classic interview topic, which stumped many people.

"If you are a data scientist at Tencent, what percentage of articles on WeChat recently are rumors?"

Most people's first reaction is to think about the "answer". What percentage? But if you think so, you fall into the eyes of this question.

As the best data scientist, you should be logical and thoughtful. First of all, you should think about how to define "rumors" and what indicators to use to calculate them. Next, you need a simple formula to visualize this indicator and the data you can collect.

This question is open-ended, and there is no completely correct answer, because everyone has different definitions and indicators of "rumors", and those with rumor keywords belong to "rumors"?

Are rumors from unknown authors and websites? Are rumors forwarded by people with low academic qualifications? Perhaps in your professional field, you can use complex software, formulas and text analysis to get the most correct answer, but in the interview, the interviewer only needs to know your solution ideas.