2022年的热门工作：数据科学家

    十年之后，决定投身应用程序开发行业的技术精英们可能会后悔当初没上一两堂应用数学类课程。即将到来的数据洪流（稍后将展开介绍这方面的内容）将催生出一波全新的需求，对计算机科学家的需求。他们既是数学家，又是产品开发专家，同时还是侦探。

    D•J•帕蒂尔是数据科学领域的先驱。这是一门新兴学科，旨在组织并理解由机器生成的所有数据。未来十年内，这个挑战将呈指数级增长。

    目前，大约有4亿台设备连接到互联网上，其中大部分是手机和电脑。到2020年，约500亿台涵盖汽车到家电的各色设备将彼此联通。届时，各公司将需要像帕蒂尔这样的数据科学家团队，整理从互联网库存指标到客户发布的Twitter消息等各种数据。这个角色非常重要，以至于风投基金Greylock Partners已经聘请帕蒂尔担任“常驻数据科学家”，帮助投资对象发掘自身的数据，从中找出有用的模式和统计数字，帮助它们提高效率，提升决策水平，超越竞争对手。

    帕蒂尔曾经在商务社交网站LinkedIn担任了三年的首席科学家。他深知科学数据的商业价值，只不过他把数学家的逻辑成功运用到了这项工作中。他的口头禅是：“量化问题，尔后才能解决问题。”

    译者：项航

    A decade from now the smart techies who decided to become app developers may wish they had taken an applied-mathematics class or two. The coming deluge of data (more on that in a moment) will create demand for a new kind of computer scientist -- a gig that's one part mathematician, one part product-development guru, and one part detective.

    D.J. Patil is a pioneer in the field of data science, a new discipline that aims to organize and make sense of all the data generated by machines. It's a challenge that will grow exponentially over the next decade.

    Today there are some 400 million devices connected to the Internet, mostly phones and computers. By 2020 some 50 billion devices, from cars to appliances, will be talking to one another. And companies will need teams of data scientists like Patil to sort through everything from internal inventory metrics to customer tweets. The role is so important that Greylock Partners has hired Patil to serve as a "data scientist in residence" to help its portfolio companies mine their data for patterns or stats that will make them more efficient or smarter than their competitors.

    Patil understands the business value of data science -- he was LinkedIn's (LNKD) chief scientist for three years -- but he brings a mathematician's logic to the job. His mantra? "If you can't measure it, you can't fix it."