Skin cutaneous melanoma (SKCM) is a cancer formed by the malignant transformation of melanocytes in the basal layer of the skin. Reactive oxygen species (ROS) are thought to be a significant factor influencing tumor development, yet the link between SKCM and ROS is still unclear. Four datasets (TCGA-SKCM and GEO-GSE19234, GSE54467, and GSE65904) were adapted to perform multi-omics analysis. A total of 28 prognostic ROS-related genes (ROSRGs) were identified, and consensus clustering analysis was conducted to elucidate the prognostic value of ROSRGs in SKCM. ssGSEA and GSVA analyses were used to explore the potential biological and immunological implications of ROS clusters in SKCM patients. In addition, we built and validated a risk prognostic model for the ROSRGs signature in SKCM. The results indicated significantly shorter survival times for high-risk patients. The applicability of the established ROSRG signature to different patient populations was also demonstrated in the study. Go, KEGG, and mutation analysis were employed to explore the functions of the 446 DEGs. We used various algorithms to examine immune cell infiltration to discover insights into the immune microenvironment of SKCM. The high-risk group was also found to exhibit lower TIDE scores, suggesting the possibility of higher responsiveness to immunotherapy. Besides, we explored the possibility of personalized therapy regimens based on patient subgroups. Finally, we gain further insight into the immune microenvironment of SKCM at the single-cell level. Signature expression levels were higher in monocytes, macrophages, and B cells. In Conclusion, we explored the relationship between SKCM and ROS through multi-omics approaches and further investigated potential immune checkpoints in SKCM and genes affecting tumor heterogeneity in SKCM. Our findings provided novel ideas for personalized clinical treatment of SKCM patients and new evidence for improving the prognosis and preventing metastasis in SKCM patients.