When enterprises face a large amount of enterprise data, how to effectively utilize a large amount of information to better manage talent has become a key issue that urgently needs to be solved. Therefore, this article proposes a human resource decision-making optimization method based on the Hadoop big data platform. By taking steps such as data collection, feature extraction, model construction, and decision optimization, the scientificity and accuracy of enterprise human resource management can be improved. This article compares the performance of the algorithm used with machine learning (ML) and deep learning (DL) algorithms, and the results indicate that the F1 value of the method designed in this article is 95.8%, which is higher than 84.7% of DL and 77.9% of ML. Experiments have shown that this method can effectively enhance the accuracy and efficiency of human resource decision-making, providing strong support for human resource management in enterprises.