Big Data: 21st Century Hottest Careers

According to Google trends, "big data" is rarely used as a search term in 2011, but since the beginning of 2012, you can almost hear people in all walks of life talking about "big data".

This is a very fast growing area, and it has spawned a lot of jobs. A  report predicts that by 2018 only the United States will have a gap between 140,000 and 180,000 people in the "in-depth analysis" of large data professionals. According to a new Vantage company survey of Fortune 500, 85% of the top 500 companies have either launched big data projects or are planning to launch them. Their investment in data analysis will rise by an average of 36% over the next few years. No wonder the Harvard Business Review article called Data analysis "the hottest job of the 21st century." ”

One of the first things to know about people who are interested in entering the "Big data" profession is what their career thresholds are. The problem seems simple and complex. Large data areas are developing very quickly, and the recruitment standards of companies are diverse. For example, some employers may require you to master a particular programming language, but some companies simply do not have that requirement. In this regard, the expectations of the Chinese and American companies for large data professionals reflect a number of different characteristics.

We first look at the domestic, online search for "data analyst" This position, Baidu showed the latest recruitment information about nearly 9,000. For example, the recruitment requirements of one of the "nationally renowned mobile reading companies" require that candidates meet:

· More than three years working experience, at least 1-2 successful medium project experience;

· Excellent Business Analysis Report writing ability, be able to discover and analyze the implicit problem in time;

· At least one data analysis tool (R/sas/spss/matlab) is mastered to realize the optimization algorithm;

· At least familiar with a database, skilled use of SQL, has a wealth of data analysis, mining, cleaning and modeling experience;

· Proficiency in the use of java/c++/python/php to build a medium-sized data analysis system, has a wealth of scripting data experience.

Then look at Baidu's own recruitment data analyst job Requirements:

· Statistics, mathematics, data mining and other major;

· More than two years working experience in Internet Industry analysis field is preferred;

· Solid machine learning/NLP theory and technology base, skilled use of spss/sas/matlab tools;

· Excellent verbal and written communication skills;

· Ability to work in UNIX environment, able to use scripting languages such as Shell/python is preferred;

· Excellent analytical and problem solving skills, passionate about solving challenging problems;

· Good logical thinking ability, strong learning ability.

A number of other companies in the relevant job recruitment requirements, in general, the most important quality of domestic companies summed up: proficiency in the use of data analysis tools (Master Spss/sas/matlab is the basic skills, some companies will increase the specific requirements); Have 2-3 years of working experience, digital sensitivity, analytical skills, Strong expression Ability. These qualities are important in data analysis. But the problem is that the big data boom is what happened in the last two years, where can the talent market quickly produce so many candidates that meet expectations?

Some companies in the United States have come to realize this by taking a more realistic approach: on the one hand, working with universities to develop large data professionals and research in the long term, such as the establishment of a large data science and technology Centre by Intel in collaboration with the MIT Institute of Data Sciences; BM has invested 100 million of dollars in China's universities to promote large data education, has been with Beijing Polytechnic University, Fudan University, Peking University and other 7 universities to reach cooperation.

On the other hand, the business community has begun to shift its mind, instead of looking to find an omnipotent genius to handle all the data analysis work, but to attract more talented people to form a creative problem-solving team. Some do not even need to have a specific professional background such as statistics.

So for those who want to enter this business, don't be discouraged, even if not computer or math trained, you still have a chance. "If you're not a pure math person, or a professional programmer, that's okay because you can work with people on the same team," says Andrew 礠, chief analyst at FICO, the leading U.S. data industry. In addition to quantitative analysis, we need people with knowledge and curiosity, and people who can point out business problems and communicate with customers. ”

Finally, let's take a look at how the industry returns. With large data professionals still in demand over supply, a senior data scientist in the United States can earn 175,000 of millions of dollars in a large social media enterprise, while the freelancers are up to $200.

In addition, some entrepreneurs are taking root in big data to create their own careers. "Big Data Entrepreneurship" has become a very popular trend at present. "Technological innovation and Big Data Entrepreneurship" is an important discussion unit in the "Technology Innovation and Entrepreneurship Forum" held at MIT's Sloan School of Management this May. In the United States, a company that has just been reported by Fortune is Flatiron Tiyatien, a two-Year-old founder of 28, who is trying to use large data analysis to give the best cure for cancer. The company has just won more than $100 million trillion in venture capital from Google.