抽丝剥茧：数据科学家成职场新宠

    虽然美国失业率持续在高位徘徊（7月份为9.1%），但技术界产生了一种新锐的需要高超技能的职位：数据科学家，各公司都在大力网罗此类人才。

    数据科学家帮助各公司理解其每日搜集的海量数据信息，从内部作出的销售报告，到客户发布的Twitter消息，无所不包。数据科学家们需要获取、分类整理并弄清哪些数据是有用的，他们需要同时扮演统计学家、鉴证专员以及黑客的角色。数据存储公司EMC负责营销的副总裁理查德•斯内称：“数据科学家不会仅仅看一个数据集就停止挖掘。他们需要找出数据背后的事实真相，然后向商业决策者们解释这些事实。”

    谷歌（Google）和亚马逊（Amazon）等网络公司常年设置有这个职位。但近来包括沃尔玛（Wal-Mart）和地理定位网站Foursquare在内的各类机构都在招聘能分析全部数据并提供情报，帮助优化商业决策或新产品的计算机科学专家。举例来说，希拉里•梅森是网址缩略服务提供商Bitly的首席科学家，他在帮助该公司将其海量数据打包进一个度量工具，Bitly的客户可以利用该工具跟踪了解自己的内容在网上进展如何。

    EMC今年5月在拉斯维加斯召开了首届数据科学家峰会（有300人参加），此后，数据科学就变得异常火爆起来。该行业拥有不少业内博客，Bitly的梅森创建的Dataists.com就是其中之一。斯坦福大学（Stanford University）开办的数据挖掘课程现在也很热门，去年超过120名学生注册了这门课。5年前该课程首次开放时，仅仅招揽到20名学生。

    数据挖掘课程任课老师安娜得•拉贾罗曼称：“你能从中看到大规模数据挖掘的发展情况以及大家的兴趣。许多公司都需要这样的人才，如果学生能学会这些技能，他们将非常抢手。”拉贾罗曼是沃尔玛实验室（@WalmartLabs）的负责人。该实验室隶属于沃尔玛，目前正在寻找途径，利用电子商务数据为沃尔玛零售店增加移动和社交购物功能。

    虽然目前无人知晓业界究竟有多少数据科学家，也没人清楚还需要多少，但大家一致认为，对该职业的需求将会非常强劲。最近麦肯锡全球研究所（McKinsey Global Institute）发布报告称，到2018年，美国市场对拥有数据分析技能人才的需求缺口将达19万人。商务社交网站LinkedIn产品负责人迪普•尼沙尔称：“目前市场上招聘数据工程师的难度已经超过搜索工程师。”数据科学家的工作量显然很大：IDC预计，到今年年底，个人消费者及公司将创造1.8千万亿兆字节（zettabytes）（1千万亿兆字节相当于1万亿千兆字节）数字信息。没有人能忽略如此海量的数据。

    译者：项航

    The unemployment rate in the U.S. continues to be abysmal (9.1% in July), but the tech world has spawned a new kind of highly skilled, nerdy-cool job that companies are scrambling to fill: data scientist.

    A data scientist helps companies make sense of the massive streams of digital information they collect every day, everything from internally generated sales reports to customer tweets. The gig which requires the specialist to capture, sort, and figure out what data are relevant is one part statistician, one part forensic scientist, and one part hacker. "A data scientist doesn't only look at one data set and then stop digging," says Richard Snee, a vice president of marketing at EMC (EMC), the data-storage company. "They need to find nuggets of truth in data and then explain it to the business leaders."

    Data scientists have been a fixture at online companies like Google (GOOG) and Amazon (AMZN) for years. But these days organizations as diverse as Wal-Mart (WMT) and Foursquare are hiring computer science experts who can analyze all their data and provide intelligence that leads to better business decisions or new products. At Bitly, the URL-shortening service, for example, chief scientist Hilary Mason is helping the company package some of its massive volume of data into a measurement tool that Bitly customers can use to track how their content is faring online.

    Data science has become such a hot field that EMC convened the first-ever data scientist summit in Las Vegas in May (300 people attended). The profession has its own blogs, including Dataists.com, founded by Bitly's Mason. And Stanford University's course on data mining is packed: More than 120 students registered last year; when it was first offered five years ago, just 20 signed up.

    "That shows you the growth and interest in large-scale data mining," says course instructor Anand Rajaraman, who also runs @WalmartLabs, a division of Wal-Mart that is looking at ways to use e-commerce data to add mobile and social shopping features at its retail locations. "Companies want these people, and they become more attractive if they learn the skills."

    No one currently tracks exactly how many data scientists there are, or how many will be needed, but by all accounts demand will be high. A recent report from the McKinsey Global Institute says that by 2018 the U.S. could face a shortage of up to 190,000 workers with analytical skills. "Data engineers are already harder to find than search engineers, and that's a sign of the times," says Deep Nishar, head of product at LinkedIn (LNKD). There's certainly plenty for data scientists to work with: IDC estimates consumers and companies will create 1.8 zettabytes (equal to a trillion gigabytes) of digital information by the end of the year. And that's a data point too big to ignore.