之前在QuantNet上看过一篇文章，讲金融工程需不需要读PhD，和题主的题目其实是类似的，我翻译了一下附上吧：
The Value of a PhD and MFE Degree
Since writing for this blog in January about the HFT/algo job market, I’ve received many inquiries from students asking about the “requirements” for quant jobs on Wall Street. “Do I need a PhD?” is a frequent question. Each time I receive one of these inquiries, I struggle with the answer. My instinct is no. But when I look at who is working in these jobs, I do see a predominance of PhD’s in the top positions. PhD’s in mathematics, physics, operations research, EE, etc. are common in the quant community. So it’s tempting to tell students that a PhD is helpful, but it feels like the wrong answer.
自从写了有关高频算法交易的就业市场的博客后，我收到了很多学生的询问，他们问我华尔街的“宽客”工作要求。其中一个常见问题就是“我需要PhD学位么？”每次收到这样的问题，我都要思躇良久。我的本能会说不，但是当我着眼于宽客岗位上的人时，的确会发现PhD学位在顶部职位的显著优势。在宽客群体中，拥有数学、物理、运筹、电子工程等专业的PhD学位是很普遍的。因此，答案倾向于告诉学生PhD是有帮助的，但是这个答案感觉起来又是错误的。
In my gut I know that the people getting these jobs are not getting offers because they have extra letters after their name. The people in these positions are there because they have proved over their academic and professional lives that they are:
我的直觉告诉我，得到宽客工作的人不是因为他们的名字后多了什么学位头衔，而是因为他们在学术和职业生涯中证明了他们具有以下的品质：
List 1
- Very smart
- Quantitative thinkers
- Good at figuring things out with minimal guidance
- Dedicated
非常聪明；量化思维者；善于在最少的指导下解决问题；专注
But the above is a generic list of attributes for hiring into just about any job. So what is it that makes someone hirable as a quant? The list isn’t long:
但是以上这些特征适用于任何工作。究竟什么特征才能让人胜任宽客工作呢？这份特征的名单也不长：
List 2
- Education in advanced math (stochastic calculus, statistics, probability, etc.)
- Good software development skills
- Good data analysis skills
具备高级的数学方面教育（例如随机微积分，统计学，概率论等）；擅长软件开发；优良的数据分析能力
Okay, now combine the two lists, and you have the list of qualifications for a quant.
结合这两份名单，你就可以知道成为宽客的必要条件了。
So, back to the question of whether to get a PhD. Should I get a PhD?, asks one student who is angling for a career in quantitative finance. Will it help me? Is it necessary? No, it’s definitely not necessary. Will it help? Empirically, it seems to help. But does it? I’ve finally come to clarity on the subject with the help of a conversation today with the director of a quant group supporting credit trading for a major investment bank. Of the two lists above, the important qualifications are on the first list. This list has nothing to do with your education. Your success in any field depends on the first list. The 2nd list consists of skills, skills that can come from your education or experience. They are enabling skills, but they are not dictators of success. All career success comes from differentiating oneself with respect to the elements on the first list. You can get a PhD, spend the money and the time, but if you don’t differentiate yourself in the fundamental elements of success, the PhD won’t help.
回到要不要拿到PhD学位的问题。PhD是必需的么？肯定不是。PhD有帮助么？经验上来看，似乎是有帮助，但果真如此么？我和一个负责投行信用交易支持的宽客组主管聊了这个问题，最终我有了清晰的答案。在上面两个名单中，更重要的是第一个名单里面的品质特征。这份名单与你的教育无关，而你在任何领域取得成功都依赖于这份名单。第二份名单都是些技能，而技能来自于你的教育和经历，它们能够让你有能力胜任工作，但是却不是成功的缔造者。所有的职业成功都依赖于第一份名单的因素。你可以花费时间和金钱去读PhD，但是如果你不具备成功的根本因素，PhD学位也帮不了你。
So why are there so many PhD’s in quantitative roles, anyway? I think the answer is pretty obvious. Very smart people with quantitative instincts are drawn to the PhD path. Later they find that they are well suited to a career in finance. They satisfy both lists and hence are successful in quantitative roles in finance. Almost without exception, these are individuals who pursued a PhD based on their interests and passions (EE, Physics, Applied Math, etc.), not people who pursued a PhD as a means to a job in finance. QED: A PhD is not a requirement for a career as a quant in finance.
那为什么宽客中有这么多PhD呢？我觉得答案很明显。非常聪明而且有量化直觉的人自身向往去读PhD。然后他们发现，他们非常适合在金融业工作。他们同时满足上面两个名单，因此才会在量化金融领域取得成功。几乎毫无例外地，这些人读PhD是因为兴趣和热情，而不是因为想把PhD当做进入金融业的手段。证毕：PhD学位不是从事金融宽客的必需品。
The MFE
I feel this article isn’t complete without addressing the MFE degree. The MFE provides students with the fundamental skills utilized in quantitative jobs. If you can afford it, it’s an easy way to satisfy List 2. However, it’s by no means a ticket to success in quantitative finance. I’ll explore the MFE further in my next post, “The MFE, Is it a Contra-indicator?”
我觉得如果不谈一下金融工程硕士学位，这篇文章就不完整。金工硕士学位可以提供给学生量化工作中要用到的基本技能。如果你能够负担起学费，这会是一个捷径来满足第二个名单，但它绝不是通往量化金融成功的门票。
小结：PhD学位并不是在金工领域取得成功的原因，只不过宽客天才因为喜欢顺便读了个PhD而已。想要取得成就，无论什么行业，都要做到专注、量化思维和善于解决问题，当然还要有聪明的天赋。
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