The recurrence rate of nonmelanoma skin cancer is highly related to the residual tumor after surgery. Although tissueconserving surgery, such as Mohs surgery, is a standard method for the treatment of nonmelanoma skin cancer, they are limited by lengthy and costly frozen-section histopathology. Raman spectroscopy (RS) is proving to be an objective, sensitive, and non-destructive tool for detecting skin cancer. Previous studies demonstrated the high sensitivity of RS in detecting tumor margins of basal cell carcinoma (BCC). However, those studies rely on statistical classification models and do not elucidate the skin biophysical composition. As a result, we aim to discover the biophysical differences between BCC and primary normal skin structures (including epidermis, dermis, hair follicle, sebaceous gland and fat). We obtained freshly resected ex vivo skin samples from fresh resection specimens from 14 patients undergoing Mohs surgery. Raman images were acquired from regions containing one or more structures using a custom built 830nm confocal Raman microscope. The spectra were grouped using K-means clustering analysis and annotated as either BCC or each of the five normal structures by comparing with the histopathology image of the serial section. The spectral data were then fit by a previously established biophysical model with eight primary skin constituents. Our results show that BCC has significant differences in the fit coefficients of nucleus, collagen, triolein, keratin and elastin compared with normal structures. Our study reveals RS has the potential to detect biophysical changes in resection margins, and supports the development of diagnostic algorithms for future intraoperative implementation of RS during Mohs surgery.