Seriously. Although the industry of data analysis has a natural professional contempt chain (there are real differences in the logical thinking ability of arts and sciences, the acceptance of programming languages, and the basis of mathematical statistics, which is also an important reason why Party A trusts the background of science and engineering more, because schools specializing in social science or literature and art rarely make students' curriculum training plans in strict accordance with mathematical logic), it does not mean that arts students have no chance, because before university, we have never been formally exposed to programming or statistics, and undergraduate courses are more about promotion. Therefore, friends, interests and decisions of liberal arts majors are also important factors, and we can't deny ourselves only by objective professional background.
Of course, science and engineering majors such as mathematics and applied mathematics, statistics, computer science and technology do have objective advantages over liberal arts students, but their abilities are greater than their majors, and their interests will determine how far you go. After all, data analysis is not like programming, which requires you to type code and learn many programming languages every day. Data analysis pays more attention to your practical operation and business ability. Now software learning is very simple and convenient. What really needs to be improved is our logical thinking ability, keen insight and good communication and expression ability. These are all related to their own efforts, rather than relying solely on the background of science and engineering. On the contrary, these abilities are more inclined to liberal arts students. After all, curiosity and creativity are also indispensable to a person.