数据科学家:21世纪最性感的工作。

IF 9.1 4区 管理学 Q1 BUSINESS
Harvard business review Pub Date : 2012-10-01
Thomas H Davenport, D J Patil
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引用次数: 0

摘要

早在上世纪90年代,计算机工程师和华尔街的“量化分析师”是商界的热门职业。如今,数据科学家是各家公司竞相招聘的对象。随着企业努力应对前所未有的海量和种类的信息,对这些专家的需求远远超过了供应。事实上,曾投资Facebook和LinkedIn的风投公司Greylock Partners非常担心数据科学家的短缺,因此它成立了一个招聘团队,专门为其投资组合中的企业输送数据科学家。数据科学家是实现大数据机遇的关键。他们为其带来结构,在其中发现引人注目的模式,并就产品、流程和决策的含义向高管提出建议。他们发现隐藏在数据中的故事,并与人交流。他们不只是提供报告:他们抓住问题的核心,并设计出创造性的方法来解决问题。例如,一位正在研究欺诈问题的数据科学家意识到,这类似于DNA测序问题。他将这些不同的世界结合在一起,精心设计了一个解决方案,大大减少了欺诈损失。在本文中,哈佛商学院的Davenport和Greylock的Patil深入探讨了组织需要了解哪些数据科学家:在哪里寻找他们,如何吸引和培养他们,以及如何发现一个优秀的数据科学家。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data scientist: the sexiest job of the 21st century.

Back in the 1990s, computer engineer and Wall Street "quant" were the hot occupations in business. Today data scientists are the hires firms are competing to make. As companies wrestle with unprecedented volumes and types of information, demand for these experts has raced well ahead of supply. Indeed, Greylock Partners, the VC firm that backed Facebook and LinkedIn, is so worried about the shortage of data scientists that it has a recruiting team dedicated to channeling them to the businesses in its portfolio. Data scientists are the key to realizing the opportunities presented by big data. They bring structure to it, find compelling patterns in it, and advise executives on the implications for products, processes, and decisions. They find the story buried in the data and communicate it. And they don't just deliver reports: They get at the questions at the heart of problems and devise creative approaches to them. One data scientist who was studying a fraud problem, for example, realized it was analogous to a type of DNA sequencing problem. Bringing those disparate worlds together, he crafted a solution that dramatically reduced fraud losses. In this article, Harvard Business School's Davenport and Greylock's Patil take a deep dive on what organizations need to know about data scientists: where to look for them, how to attract and develop them, and how to spot a great one.

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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
1
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