Assessing the core competencies of organizations plays a crucial role in the hiring process for startup companies. Research conducted during meetings at a high-tech startupHigh-tech startups company in its seed stage, which the author manages, has revealed the significance of the ability to embrace uncertainty. This involves the capacity to generate hypotheses without being constrained by immediate facts and methodologies. To investigate further, we employed correspondence and principal component analysis (PCA) techniques to distinguish the characteristics of employees possessing these abilities from those who do not during their conversations. Our proposed methodology involves transcribing text using deep learning, conducting text miningText mining on the transcribed data, applying PCA to identify individuals with distinct traits, and quantitatively identifying word groups that exhibit a certain degree of correlation with these traits. Furthermore, by utilizing the PCA results and constructing a feature space for distinguishing these abilities, we aim to establish a comprehensive framework that can be employed within the company on a global scale.