China needs 1.8 million data talents in the next 3 to 5 years, but as of now, there are only about 300,000 big data practitioners in China. At the same time, the criteria for selecting talent in the big data industry are constantly changing. Initially, the demand for big data talent is mainly focused on ETL research and development, system architecture development, data warehouse research and other biased hardware areas, with the majority of IT and computer background talent. With the development of big data to the extension of various vertical fields, the demand for statistics, mathematics professionals, data analysis, data mining, artificial intelligence and other software-oriented fields increased.

I, big data main employment direction

Development class and big data analysis class. Specific positions such as: big data analysts, big data engineers and so on.

"Big data analyst is to use appropriate statistical analysis methods to analyze a large amount of data collected, the emphasis is on the application of data, focusing on the statistical level content will be more. For example, as a product manager, you can build financial models through data to launch some financial products. Big data engineers, on the other hand, focus on technology, mainly around the big data platform system-level research and development, favoring the development level." Professor Hua Ying introduced, "We summarize the process of using big data analytics in business into the following steps: data acquisition and pre-processing, data storage and management, data analysis and modeling, and data visualization. In this application process, graduates can choose employment at different points according to their interests and specialties."

Two, big data work field

The current big data work field is divided into the following four major categories:

1, data development engineers: responsible for data access, data cleansing, underlying reconstruction, business theme modeling and other work; big data overall computing platform development and application;

2, data analysts: in the e-commerce, financial, and consulting industries that have industry data, Telecommunications, consulting and other industries to do business consulting, business intelligence, analysis reports.

3, data mining engineers: in the multimedia, e-commerce, search, social and other big data-related industries to do machine learning algorithms implementation and analysis.

4, scientific research direction: in colleges and universities, scientific research units, corporate research institutes and other high research institutions to study the efficiency of new algorithms to improve and future applications.