With the advancement of internet and social media, there is a huge availability of various online portals where employees express their reviews on various characteristics of their organizations. At the same time, it becomes a great challenge for a prospective employee to decide whether to join an organization or not, as there is a deluge of reviews. The present research addresses this concern by using actual employees’ review data of over 8 lakh reviews based on more than 400 UK-based organizations to develop a sentiment analysis framework using “Natural Language Processing” (NLP) and machine learning. The research addresses a multidimensional perspective, including sentiment analysis of pros and cons as mentioned by employees; topic modelling to identify the significant topics that provide insights to company’s overall culture; and emotional tones’ analysis. Finally, a regression model was developed to predict the effect of work-life balance, cultural values, career prospects, compensation, and senior management support on employee overall sentiment. The results produced an R-squared value of 0.61 that signifies that 61% of variability in sentiment is dependent on these five factors. The key contribution of this research is in the presentation of an analytics framework for sentiment analysis, providing guidance to prospective employees in choosing an organization and further suggesting actionable recommendations for organizations to improve workplace environments.