Interactions between the mean flow and eddies play a central role in shaping oceanic circulation by redistributing heat, momentum, and energy. Accurately representing these processes in General Circulation Models (GCMs) remains a challenge due to limitations in subgrid-scale parameterizations. This study highlights the constraints imposed by small ensemble sizes on capturing the Reynolds stress tensor and diagnosing its associated work—key elements for assessing mean-to-eddy energy conversion rates. To address these challenges, we employ the Location Uncertainty (LU) framework, which introduces stochastic variability into the governing equations to represent unresolved turbulent effects. Using a 48-member ensemble simulation of the North Atlantic under realistic forcing, we compare deterministic and stochastic estimates of Reynolds stress work. The LU framework improves statistical convergence and stabilizes higher-order moments, leading to a more accurate representation of energy transfer statistics. Key contributions include a novel formulation of energy transfer equations and enhanced statistical diagnostics of Reynolds stress work within the LU framework. This study provides valuable dynamical diagnostics for identifying energetic patterns and regions of stability, offering new insights into eddy–mean flow interactions in the Gulf Stream.