IT trending skill-set for Women

Data scientists are the analytics professionals responsible for acquiring, cleaning and transforming data to glean those invaluable insights. Organizations today are looking for people who possess the interests and skills that can make them successful data scientists and these skills include:it

A love for numbers : People with a background in mathematics, statistics and the sciences do well as data scientists.

Technological competence : Data scientists need to be comfortable working with computers and should possess computer coding skills. Knowledge of data technologies like Hadoop, Spark or coding languages such as Python, R and Scala is a big plus.

Elaborateness for design : The ability to translate data visually for business audiences is the key.

Rational curiosity : Good data scientists relish the idea of digging through piles of data and making connections and corollaries not readily observed.

An artistic bent : Data scientists need to be able to take the minute and create a big picture of the data they are seeing.

Interactions pros : To illustrate the value of their insights, data scientists must be able to easily articulate their findings to business people.

It is hard to know that women occupy only 25%-30% of data and analytics roles in the industry as per the recent research conducted by US-based consulting firm Innodatatics Inc.

Everyone should be able to get behind these emerging technologies. With Data Science and other emerging fields like AI, IoT, etc, we have a serious lack of qualified women data scientists (in the U.S and many other countries).  

Out in Silicon Valley, companies are hostile to hire quality data scientists; this is hurting the ability to grow companies. If as many women go into the field as men, this would be a big win for the world.

Having more women in tech now will mean more female tech leaders and more girls thinking, “Yes, this is for me.”

Women and men think differently on average. I can’t say what of that is cultural and what is organic (and it doesn’t matter for this argument), but they do, currently, think differently on average. For example, women tend to be more expressively sensitive and more compassionate. Women are also more design-focused on average. Having a firm made up of people who approach problems in different ways is good. For example, the woman on your team might be more likely to draw out the opinions of quiet people.

Although a lot of organizations have strived to accelerate the women population in STEM fields, gender diversity remains a crucial issue.

Diversity of thought is good for business.