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发帖数: 201 | 1 告诉我：你想要什么；我们告诉你：你如何作.
－ 钱？8万，10万，25万？
－ 绿卡，美国的山水？
－ 教授的头衔的荣光以及与之相伴的研究教学生活
－ 工程师，统计师，分析师，编程员，以及与这些职业相关的挑战，汗水，希望，沮
丧，成功的喜悦。。。
无休止的讨论SAS，R， Python 谁好谁差，好像就要出行的一家一味的争论是开宝马，
丰田，本田，尼桑，还是福特150，却没有人问问我们要到那里去，干什么去，又是为
什么。。。
于是我建议：
I strongly hope professionals from different industries give advices about
the industry they are familiar with in a comprehensive setting, a realistic
picture.
For example, it would be very helpful to the new students who are looking
for jobs if people from Banking, Insurance, Marketing, Quality Control,
Internet Apps, "Big Data" can provide the following info:
1) What requirements are needed to get your industry (master, phd instate,
or combinations)
2) How likely the new graduates with master/phd get those positions? For
example, in your group in a big company, do you have 2, 3, or more than 20,
or 30 such positions?
3) If you are introducing some one to your company, what improvements you
would suggest that the students should have done before the on sight
interview?
感谢网友frank1243率先支持，以下将是我从我的个人与朋友的角度的讨论，因偏居一
偶，偏见与短视难免，读者当自斟酌。
Statistics departments are growing in USA. 15 years ago, a department was
having 15, 20 students; now, many departments are having more than 100. 15
years ago, people with MS from stats were not worried too much about finding
jobs. But now, there are quite a few with ms have to wait a few months, or
one or more years before they can receive their paychecks from a standard
job.
Therefore, the situation is like this: students have to prepare very early
in order to market them well and reduce the risk of "unemployment" situation
. Back to the community where people need H1 sponsorship, it is more urgent
than any other communities.
Now, how to prepare your self for the challenges?
What are the most important things to do? What advices they need and from
whom?
Before reading on, please take a moment to tell me your preference by voting
on this poll:
http://bancova.com/?q=node/207
Now, you've voiced your opinion. But remember, that is your initial choice.
Would you change your mind after you've read the following writings from
professionals who have been in the industry for a while.
Here are some opinions for us:
A) Big Data Industry
B). 银行信用卡部门的Decision Tech Analyst
C. SAS programmers or biostatisticians in the Pharmaceutical Industry
D. Quality Control Engineer
F. Government Employees in charge of Government Statistics related tasks.
E. Professors / Teachers of Statistics in Universities or Colleges.
(Please add more …..)
Now, my call to the people who have worked in these industries, please post
what you have experienced in these areas so that students can benefit from
your posts
remember: to help the new students is to help ourselves! |
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