Women In Analytics
summary
Claims that nearly half of analytics professionals are women back up specific numbers: 53% statisticians are women, actuarial ~40%, ASA ~33%, yet conferences show 60 sessions 7 women. Examples of tools and paths include Python, Coursera courses, legacy Fortran/C++, and text analytics; one group reports building the first Business Analytics area at Aflac. Notes that automation now produces 200-300 models in minutes, recommends using analytics to track promotions and design non‑linear return‑to‑work interventions so women stay visible and progress.
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chapters (7)
- 0:00Start
- 3:45Are There Enough Women in Analytics in the Us ...
- 10:23Skills Needed
- 13:44The Reasons Why Women Are Not Visible in Analytics
- 19:28Shoutouts
- 23:35Holding Everyone Accountable
- 27:55The Difference between a Male and a Female Resume
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