Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic UV light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19, and ARID2), three of which—RAC1, PPP6C, and STK19—harbored recurrent and potentially targetable mutations. Integration with chromosomal copy number data contextualized the landscape of driver mutations, providing oncogenic insights in BRAF- and NRAS-driven melanoma as well as those without known NRAS/BRAF mutations. The landscape also clarified a mutational basis for RB and p53 pathway deregulation in this malignancy. Finally, the spectrum of driver mutations provided unequivocal genomic evidence for a direct mutagenic role of UV light in melanoma pathogenesis. Display omitted ► Landscape of driver mutations by exon sequencing of 121 melanoma tumor/normal pairs ► Method for detecting genes with driver mutations in high-mutation-rate setting ► PPP6C, RAC1, SNX31, TACC1, STK19, and ARID2 are significantly mutated melanoma genes ► Signature spectrum of UV mutagenesis accounts for 46% of driver mutations found A statistical approach for analyzing exome sequencing data differentiates between driver mutations and the abundant passenger mutations found in melanoma due to UV light exposure. Analysis of whole-exome sequence data from 121 tumors identifies six new melanoma genes and defines a landscape of driver mutations in this challenging malignancy.