Developing accurate models of water for use in computer simulations is important for the study of many chemical and biological systems, including lipid bilayer self-assembly. The large temporal and spatial scales needed to study such self-assembly have led to the development and application of coarse-grained models for the lipid lipid, lipid solvent, and solvent solvent interactions. Unfortunately, popular center-of-mass-based coarse-graining techniques are limited to modeling water with one water per be ad. In this work, we have utilized the K-means algorithm to determine the optimal clustering of waters to allow the mapping of multiple waters to single coarse-grained beads. Through the study of a simple mixture between water and an amphiphilic solute (1-pentanol), we find a four-water bead model has the optimal balance between computational efficiency and accurate solvation and structural properties when compared to water models ranging from one to nine waters per bead. The four-water model was subsequently utilized in studies of the solvation of hexadecanoic acid and the structure, as measured via radial distribution functions, for the hydrophobic tails and the bulk water phase were found to agree well with experimental data and their atomistic target.