International supply chain projects operate in an ever-complex and uncertain world, in which conventional risk management strategies are often inadequate. This study fed on how big data analytics can be used as part of project management to optimise the management of risk on international supply chain projects. Based on an integrative qualitative methodology and a structured synthesis of existing frameworks, the research considers the role of analytics in risk identification, assessment, and mitigation improvement on global supply networks. The results suggest real-time information integration, predictive analytics, and analytics-enabled project management information systems can provide significant decision-making accuracy, governance transparency and project resilience. The study further stresses the importance of the combined implementation of complementary digital technologies in enhancing effective proactive risk management and sustainable project results. By locating project management as one of the key mechanisms to operationalize analytics-driven risk optimization, this paper offers an integrated view to bridge between supply chain management and project risk management. The study also outlines some managerial implications, limitations, and future research directions in the context of analytics-enabled international supply chain projects.