Career is a key stage for a person to realize his own value. However, with the development of society and the continuous change of organizations, the traditional career stability is getting smaller and smaller, and career planning becomes more and more important. This paper combines computer data simulation technology to analyze college students’ career planning, and puts forward a structural optimization design method based on parallel computing and genetic algorithm. Moreover, this paper uses Python to realize the computer simulation analysis of college students’ career planning data, uses adaptive genetic algorithm as the data processing algorithm, and constructs the career planning system model from three dimensions: self-management, organizational support and environmental penetration. From the experimental evaluation results, it can be seen that the college students’ career planning system proposed in this paper has good results, can effectively guide college students’ study and life, and has an important role in promoting the cultivation of college students’ good values.