亲爱的安妮：我恐怕要被一家大型投行裁员了（公司最近宣布要进行重组），我不想再去找另一个华尔街的工作，而是想进入其它领域。传统经验告诉我们，如果要转行的话，尽量去那些增长空间大的行业。我近来读到一些报道，说大数据的使用在企业界呈现激增之势。我在想，进入那个领域有什么要求吗？

    我有一些关于计量经济建模的工作经验，而且我在工作中也学习了一些基本的编程技术，不过我既不是统计学家，也不是数学家或是软件专家。我还有机会吗？那些寻找大数据人才的雇主需要我们具备哪些技能？——“我不是爱因斯坦”

    “不是爱因斯坦”：有一点你说得很对，所谓的大数据——又叫做数据分析或预测分析，是一个增长非常迅速的领域，而且催生出了很多的工作机会。根据就业市场分析公司Wanted Analytics的统计，目前网络上招聘数据分析师的广告一共有31000多条，比2011年4月猛增了46%，如果从2009年4月算起，上涨了246%。这些招聘广告里给出的年薪从73450美元到89750美元不等。（可能要比你在华尔街挣得少很多，不过你可能已经知道，华尔街几乎到处都可能要减薪，对吧？）

    很明显，对大数据人才的需求将继续迅猛增长。据一家名叫New Vantage Partners的咨询公司最近对“财富美国500强”企业的调查显示，85%的500强企业要么已经推出了大数据项目，要么正打算这么做，而且在未来几年里，他们花在数据分析上的投资将平均上涨36%。无怪乎《哈佛商业评论》（Harvard Business Review）在去年十月的一篇文章中，将数据分析称做“21世纪最热门的职业。”

    行业龙头费埃哲公司（FICO）的首席分析官安德鲁•詹宁思指出：“目前对数据学家的需求显然超过了供给，这种现象已经出现了几年了。”费埃哲公司的总部位于美国的圣何塞，主要负责为政府机构和银行、保险、医疗、零售等行业的客户运作大数据项目。该公司目前约有250名数据学家。詹宁斯还表示：“我们一直想招聘更多的数据学家。”

    要想找到这样一份工作，必须满足什么条件呢？这个问题看似简单，实则复杂。大数据领域的发展非常迅速，而且要求一些不同寻常的技能组合，各个公司的招聘标准也是五花八门。比如有些雇主可能要求你掌握某种特定的编程语言，但有些公司就根本没有这种要求。

    费埃哲公司自己就是一个例子。如果你应聘这家公司的话，你的计量建模和基础编程能力将会为你加分不少。詹宁斯表示：“我们通常会招聘有某些量化分析背景的人，从纯粹的数学和工程学背景，到统计学和计量建模背景都可以。如果你能够写编码，把数据集链接到一块儿，对于应聘也是有帮助的。”詹宁斯自己就是学计量经济学出身。

    Dear Annie: I am expecting to be laid off by a major investment bank (as part of a restructuring the company recently announced) and, instead of trying to find another Wall Street job, I'd like to go into some other business. The conventional wisdom about changing careers is, go where there is lots of growth, and I keep reading about the explosion in companies' use of Big Data, so I'm wondering: What would it take to get a foot in the door in that field?

    I have some on-the-job experience with econometric modeling, and I've picked up some basic programming skills along the way, but I'm neither a statistician, a mathematician, nor a software expert. Do I have a shot anyway? What skills are Big Data employers looking for? -- No Einstein

    Dear N.E.: You're certainly right that Big Data -- also called data analytics or predictive analytics -- is growing fast and generating loads of new jobs. Online help-wanted ads for data analysis mavens have shot up 46% since April 2011, and 246% since April 2009, to over 31,000 openings now, according to job-market trackers Wanted Analytics. Salaries mentioned in those job ads range from $73,450 to $89,750. (That's probably a lot less than you've been making on Wall Street -- but then, you already know that almost anywhere you go from there is likely to involve a pay cut, right?)

    The phenomenal growth in demand for Big Data talent is apparently set to continue. A recent survey of Fortune 500 companies, by consultants New Vantage Partners, found that 85% have either launched Big Data projects or are planning to do so, and that their spending on data analysis will jump by an average of 36% over the next several years. No wonder, then, thatHarvard Business Review, in an article last October, called data analytics "the sexiest job of the 21st century."

    "Demand for data scientists is definitely outstripping supply," notes Andrew Jennings. "It has been for a few years now." Jennings is chief analytics officer at FICO, one of the giants in the industry. Based in San Jose, FICO tackles Big Data projects for clients in banking, insurance, health care, retail, and government agencies worldwide. The firm now employs about 250 data scientists and, says Jennings, "we're looking for more all the time."

    So what does it take to get one of those jobs? That's a more complicated question than it might seem. The field has grown so quickly and seems to call for such unusual combinations of skills, that specific hiring criteria are all over the map. For instance, some employers require you to know a particular set of programming languages, while others couldn't care less.

    FICO (FICO) is a case in point. On the one hand, if you apply there, your experience with econometric modeling and basic programming could come in handy. "We usually hire people with some quant background, from pure math and engineering to statistics to econometric models," says Jennings, whose own background is in econometrics. "It also helps to be able to write enough code to link data sets together."