What is data analysis? Data analysis refers to the use of appropriate statistical analysis methods to analyze, summarize, understand and digest a large number of collected data, so as to maximize the function of data and give full play to the role of data. Simply put, it is to solve any business problem through data.

The most important ability of a business person is not what skills and knowledge you have, but the ability to solve problems. The premise of solving problems is to find problems, and data analysis can accomplish the mission of finding and solving problems.

In the increasingly research-oriented recruitment environment, whether you are a student about to enter the business positions of Internet products and operations, or a practitioner with 1-5 years of experience in operations, products, marketing and new media, data analysis ability has become an important assessment point for business personnel by employers.

Under the influence of this year's epidemic, compared with the wailing of job hunting in the traditional financial industry, the starting salary of technology is really fragrant. According to the employment report of the first master of data science graduates on 20 19, the average salary of graduates reached 27w, mainly in the fields of Internet, financial technology and quantification.

With the gradual penetration of big data technology into all walks of life, data science talents will usher in a wave of dividends. For non-engineering students who want to combine business and technology in their work, data analysis (including big data) is undoubtedly a good choice.

Today, I will share with you the basic situation of several popular industry data analysis positions:

Internet representatives: Ali, Tencent, Baidu, JD.COM, ByteDance, Pinduoduo, Didi, Meituan, shopee, etc.

1) difficulty coefficient: ☆ ☆ ☆ ☆ ☆.

2) Skills requirements:

Let's take a look at Tencent's data analysis job requirements.

Combined with previous interview experience, the skills of Internet data analysis include:

A. proficient in SQL, preferably Hive-sql.

B. be familiar with statistical theory: statistical description and inference statistics, ABtest is almost a must for interviews.

C. machine learning, this part also needs simple preparation, such as basic machine models such as logistic regression, decision tree, random forest, SVM, xgboost, etc. Of course, the foundation of python is also necessary.

D. Cognition of business, the most important purpose of data analysis is to support the landing of business, so cognition of business is the starting point of data analysis. For fresh graduates, it is best to have internship experience and have a deeper understanding of business thinking. If there is no internship, they should know more about some theoretical knowledge, such as the piracy model in the product field and the analysis of user behavior. And even use some structured thinking of consulting case practice to strengthen their analytical ability in this respect.

3) Wage level

The salary of data analysis is generally between product post and development/algorithm post, and the starting salary of several posts in different Internet companies ranges from 22w to 30w+.

Representatives of technology and finance Science and Technology in Banking Finance: Technology management students such as China Bank, China Construction Bank, China Industrial and Commercial Bank, Bank of Communications, China Merchants Bank and Ping An Bank are recruiting, and their technology subsidiaries (such as Jianxin Financial Technology) are also recruiting.

1) difficulty coefficient: ☆☆☆☆☆☆, banks have been recruited by senior universities over the years. With the development of information technology in recent years, jobs related to financial technology have mushroomed. Of course, the technical difficulty coefficient of bank technical posts is lower than that of the Internet. There was a classmate's joke before, and he took the offer of CCB's science and technology post. "The written test didn't work, and the interview blew, so I took the offer." The following is the recruitment plan of CCB in the spring of 2065438+2009. The demand for "technical talents" in many branches has reached three figures.

Easy entry+high starting salary+low performance pressure+low unemployment risk, isn't it delicious?

2) Job requirements:

Take the post responsibility of data direction of Information Science and Technology University of China Construction Bank as an example;

The skills of scientific and technological posts in banks mainly have two characteristics:

First, skill requirements, some data posts are more inclined to data development, and daily work may deal with data construction and data platforms;

The second is the distribution method, which may be unified recruitment and centralized division. For example, data posts may not be subdivided into specific data posts (such as data development/analysis/mining, etc.). ), but it may be assigned to the business department or the middle and back office department after entering.

3) Wage level

This is related to the nature of the bank itself. The starting salary of financial science and technology posts in state-owned banks is not too high, but the work intensity is low and the benefits are good (unit renting, transportation subsidies, catering subsidies, no 996, etc.). ); The financial technology of joint-stock banks, such as China Merchants Bank, is as fierce as the Internet, and of course the salary is not lower than the Internet.

Brokerage Fund Brokerage Fund Representatives: southern fund, harvest fund, Admiralty, Jiukun, Kuande and many other brokers.

There are two main categories in this category, one is data engineers in financial institutions, and the other is financial engineering. What data engineers do is similar to that of traditional data development engineers, and there is no significant advantage in salary, so here we will focus on financial engineering positions.

Difficulty, Difficulty In recent years, using artificial intelligence to mine quantitative factors and build stock selection strategies has become a hot spot in the industry. Both sellers and buyers are trying to do this, so graduates majoring in data science also have the opportunity to enter the quantitative field. However, the difficulty lies in the fact that graduates majoring in financial engineering are also proficient in this field and have comprehensive financial knowledge, so the competition is fierce.

2) Job requirements:

This is the position of financial data mining engineer of Huaxia Fund:

There are three main requirements:

A. Must be proficient in a programming language, Python/Matlab/C++;

B. have the ability to analyze financial data;

C be familiar with statistical model and machine learning model, understand the principle, and be able to realize package adjustment, preferably modeling.

3) Wage level

There is basically no upper limit on the salary of brokerage funds, and the basic salary is mostly around 20w according to individual performance.

Institutions are representatives of institutions: Shanghai Stock Exchange Technology, Shenzhen Stock Exchange Financial Technology, Shenzhen Municipal/District Government and its research institutes.

1) difficulty: it is not easy to evaluate, there are few samples around, and the technical difficulty may be lower than that of the Internet. However, due to the small number of recruitment places, the actual competition ratio is actually not low, and at the same time, it will pay more attention to academic background.

2) Salary level: basically equivalent to that of civil servants. The treatment of civil servants and institutions in first-tier cities is not low, and there are fewer opportunities for overtime unemployment. It can be said that it is a very cost-effective job. Forget it, just two words, envy.