It usually takes less than 30 seconds to browse a resume. If the resume hits the key words that the business side values, the pass rate will be greatly improved. At present, the common ability keywords are user portrait, label system, index system, monitoring system, ab experiment, user hierarchical operation, channel analysis, roi optimization, growth model, recommendation (distribution) strategy and so on.

You can also refer to the specific position jd and write some of the above keywords in the appropriate place on your resume. Each type of business, different departments pay different attention to keywords, so we should analyze and add keywords according to different business needs.

2. Quantification of outputs

Resume needs to focus on the quantification of output.

A very important duty of data analysts is to use data for business insight, business measurement and business guidance, so quantification is a professional habit; Make it clear that you are responsible for the output of the business, and the digital expression will be more convincing; I understand that some of the daily work of data analysts is difficult to quantify, which requires us to actively track the effect and function of our output data, communicate with business parties more, and get quantitative index results.

3. Project selection

Considering the following principles, choose 2-4 items to write in your resume.

Choose the project that you are most familiar with, the project with the largest output value, and the project that best reflects the analysis &; Improve the ability of the project and choose the project that best matches the company's business and has reusable methodology.

4, the embodiment of action

What analytical methods are used to focus on the embodiment of action in both project description and work experience description? How to popularize the conclusion of analysis? Describe actions more and highlight your subjective initiative.

What are the points for attention about the resume of data analysts? Ivy Bian Xiao will share with you here. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.