In this repository, I did analysis on job postings from EY's official website through web scraping and exploratory data analysis. This project is completed in collaboration with the pyschological consulting team. We have analyzed the usage of masculinary and feminine words, then identified its relationship with salary and seniority level. We have found the following:
- On an average, every job bulletin consists of about 23 feminine keywords and about 34 masculine words. This means that use of masculine keywords is more frequent than the feminine keywords in the EY job Bulletines
- At an overall level, more than 85% of the jobs have more masculine content, very few jobs have feminine bias
- Jobs related to Finance and high-level position, such as managers, show high masculine bias
- The job roles in this graph suggest that IT or Technology realted jobs also have very high levels of unconscious gender bias, For example Software Engineer, Machine Learning Engineers, are all one of the high masculine oriented jobs
- Jobs having higher value of gender bias (Orange Box) score have almost greater or equal to average salary offered