Jupyter Notebook Analysis of Salary Data Spreadsheet (opens in new tab)

- Do they hear about the same jobs? Are there differences in their job-seeking networks?

- Do they apply for the same jobs? (Are they even interested in the same jobs? Does the same job with two different job descriptions get different ratios of applications?)

- Do their resumes differ in style or substance (despite identical backgrounds)?

- Do they get the same number of interview offers for the same positions?

- Is their post-interview experience different? (offers, of course, but also benefits discussions and pay negotiations)

- Do they accept identical offers at the same rates?

It would be really interesting to look at this data, but I wonder how easy it would be to gather.

> Although additional research in this area is clearly needed, this study leads to the unambiguous conclusion that the differences in the compensation of men and women are the result of a multitude of factors and that the raw wage gap should not be used as the basis to justify corrective action. Indeed, there may be nothing to correct. The differences in raw wages may be almost entirely the result of the individual choices being made by both male and female workers.[21]

– U.S. Department of Labor as cited by Wikipedia https://en.wikipedia.org/wiki/Gender_pay_gap

Our company is almost 50/50 for male/female, with our engineering team being 100% male. At the last company I worked for in the Tampa area of FL, we had one female developer who was MTF, and we did get one female applicant to an open position, who wasn't hired because she was deemed too junior. This was for a junior position, and I think the CEO was just being unknowingly sexist.