The sexiest career in the 21st Century: data scientists

Source: Internet
Author: User

Harvard Business comments, an authoritative sexual affairs authority, announced that "data scientists" are the sexiest profession in the 21st century. The so-called sexiness not only represents the temptation to be difficult to name, but also shows that everyone does not know what it is.

No matter what the boss does not understand what data scientists do, the demand for this position has rapidly increased in recent years. The data in can be used as evidence.

But where is it? What is a data scientist? Are they scientists? Or an engineer? Programmer? Or is it a new lineage of business decision-making and innovator? does not reflect the fact that although the subject of this profession has been brewing for a long time in academia, it has not yet become a new discipline. However, this long period of academic incubator may be closely related to today's data science practices.

First, let's briefly review this history. As early as the 1960s S, Peter Naur proposed to replace "Computer Science" with "Data Science and datalogy" for the first time )", later, it was used by the alliance of international classification societies in the 1990s S. In 2001, William S. Cleveland proposed setting it up as a new discipline, absorbing "computing progress in data" as an extension of statistics. Data Science (
Data Science Journal) and 《
The Journal of data science was released on July 15, 2002 and July 15, 2003, respectively. on 2005, the National Science Commission published the Long live of digital data collection: Promoting research and education in the 21st century. In this article, data scientists were defined as "information and computer scientists, database and software engineers and programmers, subject experts, and key figures for successful management of digital data collection."

In the middle of the first decade of this century, data science was no longer regarded as a list of details of other disciplines and began to go out of the academic Hall. Troy sadkowsky completed this step in 2009. He works in an academic position in Australia, but has a title of "scientific programmer". His role is to develop applications that support large-scale, "Big Data" scientific research. In January 2009, the cross-organization working group on digital data published a report titled driving the power of digital data in science and society. sadkowsky learned the word "data scientist, I think this word is the best description of my work. September 6, 2009
He established a data scientist group on LinkedIn as a helper for his website.

However, the large-scale migration of data science from academics to the industry has long been happening in the United States. At that time, web companies were developing big data technologies and quantitative analysts needed to mine and use the massive data they collected. The number of analysts who don't want to stay in the ivory tower will all go to Wall Street. However, in 2008, the temptation of this place declined. D.j., a data scientist at Greylock partners. patil and Jeff hammerbacher set up data and analysis groups on Facebook and likedin. This move is seen as a sign of the professionalization of data science, the role of the group is to apply data that can have immediate and large-scale impact on the business. Data scientists are people who use data and science to create new things.

The title of data scientist was first mentioned by natahn Yau in 2009. He believes that data scientists can analyze data from large data sets, persons who provide things that can be used by non-data experts.

Data scientist and entrepreneur Mike Driscoll believes that data geeks have three personalities: Modeling, conversion, and visualization. A more poetic expression is: data scientists are like the combination of an explorer with high eyes and a big detective who doubts everything.

In the article "data scientist: the sexiest profession in the 21st century, jonathan Goldman, a data scientist who designed LinkedIn's "people you may know" function, may be the best way to interpret how data scientists work: first, building a theory and validating a hunch, then look for an out-of-stock mode to predict which network of someone should be launched. The work of data scientists is summarized as follows:

Data scientists explore data while exploring data. They are strongly curious-they are eager to find the core of the problem and investigate the essence of the problem, and extract these things into a set of clear and verifiable assumptions. This often reminds people of the characteristics of the most creative scientists in any field. Obviously, the title of a scientist is suitable for this emerging role. To improve their value, they rely not on making reports or PPT reports to executives, but on innovation in customer-oriented products and processes.

However, this section is still not concise and clear. Based on the above observations, we will give a concise definition of a data scientist:

Data scientists are engineers who use scientific methods and data mining tools to find new data insights.

The scientific approach is to design assumptions, test ideas, design experiments, and verify by others. These are the knowledge they have learned from statistics and scientific experience. The use of tools comes from their engineering experience, or, more specifically, from their background in computer science and programming. The best data scientist is the innovator of products and processes, and sometimes the developer of new data mining tools.

What is sexiness.

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