Harassment In The Pakistan Workplace Environment

With that said, we will also submit we are in the middle of a generational confluence where older generations have historically less interaction with technology than younger generations.

Imagine that there would be no reason to bring new “qualified or skilled” people since all (males and females) have the knowledge and skills or be able to do the current jobs; Data analytics implies more than statistical/math knowledge like intuition and that is an important skill that women have it naturally.

Computerization and automation to analyze big data in order to push products, services, money, people, places, and things for an ever-expanding civilization. Women may have the talent but not the training. Part of the issue is related to a growing hiring skew away from (Bio)statistics in favor of Engineering and Computer Science, which is more male-dominated than (Bio)statistics. The expanding echo camber in data science that evangelizes trendy methodologies like ‘deep learning’ and ‘machine learning to the exclusion of everything else (as if time series, for example, couldn’t form accurate predictions) and the lack of awareness that (Bio)statistics programs teach machine learning and coding explicitly as core classes and also not as an end but as a means to completing every homework assignment must be addressed if we are to draw new hires from increasingly neglected core Data Science programs more greatly represented by women. Women tend to be multi-functional and detail-oriented much more so than men and women have the patience needed for IT jobs.

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