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In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The results are as follows: By comparing the application evaluation of linear regression method, BP neural network and DBN model, this paper finds that DBN model has better accuracy and lower error and has better advantages in the application of college students' employment data management characteristics. In addition, the development of social economy and the number of college graduates are the key factors for the employment rate of college students. Therefore, this paper suggests that through the use of big data technology, college will build a data platform for college students' employment management and provide a carrier for college students to obtain professional information and employment management information.

Big Data Analysis and Modeling Method of College Student Employment Management Based on Deep Learning Model