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I often receive phone calls from organizations, aspiring data scientists and reporters about whether data science would be a good career choice for women. My response is absolutely yes, for the following reasons:

Women are great contrarian thinkers. One goal of data science is to find unknown truths in a variety of data sources that add value to an organization. In my experience the best data scientists challenge existing assumptions and think differently. The very best data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes.

Women are great communicators. The ability to effectively communicate data science results with decision-makers is paramount. While all data scientists have some grounding in the scientific method, computer science, modeling, statistics, data analytics, math and business acumen, the key skill that separates great from good data scientists is critical contrarian and analytical thinking along with the ability to communicate with both team members and organization leaders to achieve the goal of optimal decision-making.

Women are great team players. Data science is a team sport with many areas of expertise and strong communication and team-work skills are critical for high performing data science teams. Further, data scientists are part of a bigger team in any organization. This includes business and IT leaders, middle management and front-line employees.

In my experience, the best data scientists do not have the strongest technical skills. Rather, they are team players: professionals who love to play with data, spot trends and learn truths few others know. Most importantly, they have strong communication skills to help leaders - and all members of an organization - apply data science and analytic results to critical issues.

The goal is to use data science to help organizations turn data into information - information into knowledge and insights - and valuable, actionable insights into better decision-making and game changing strategies. Women have the potential to be among the best data scientists and I predict many will become effective future leaders in the profession.  

See: http://bit.ly/1kXsipc

Views: 11522

Tags: Data, Scientist, Women

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Comment by Susan Scrupski on March 2, 2015 at 12:45pm

We are particularly interested in women who want to join our team.  If there are women reading this post interested in applying their data science knowledge to solve a large problem for women in society (domestic violence and abuse), we'd love to talk to you.  

Comment by Kelly Li on March 2, 2015 at 5:24am

This is quite amazing haha !

Comment by Carenne Ludena on March 1, 2015 at 11:14am

Great topic! I think actually gender should not be at the heart of the issue. For data science, as for any other profesional activity, what is required is a certain number of skills. Team work, communication abilities, technical abilities (I do agree that tech skills in data science, not necesarilly programing, but certainly technical are basic!), and "thinking different", that is, giving new insights as to what the fundamental questions are and how to go about  solving them, are all very important for data science. Sometimes you find this in women, sometimes in men. What I think is really great of this discussion is that  because it is considered a high level technical domain, women are somewhat disregarded by some, which of course is nonsense. So, bref, as french would say: yes! data science is a great career choice both for women and for men,

Comment by Pradyumna S. Upadrashta on February 28, 2015 at 12:34am

"...data scientists creating their start-up have better chances to succeed with business acumen and domain expertise, than deep technical expertise. "

True.  There was recently an article that mentioned that GQ (Guts Quotient) is more important IQ.  I think what you're calling domain knowledge, is to me also a technical skill, as opposed to knowing how to code, per se.  I think the trend in programming is really to write code that looks more and more like natural conversational english.  The future of coding will perhaps be to speak in a very natural conversational style and have the compiler figure out how to convert that to assembly language.  Languages like Scala are bringing us closer to that form of natural human-to-machine communication.

Comment by Vincent Granville on February 27, 2015 at 4:42pm

Pradyumma, data scientists creating their start-up have better chances to succeed with business acumen and domain expertise, than deep technical expertise. In my case, many times, I make applications communicate with each other to leverage and operationalize data, frequently without writing code.

Comment by Pradyumna S. Upadrashta on February 27, 2015 at 12:25pm

It should also be made explicitly clear that women can be absolutely strong technical leaders.  Technical skills are not exclusive to men.

Please see:

http://en.wikipedia.org/wiki/Women_in_science

(...of which my personal favorite is Marie Sklodowska-Curie, whose biography was the first bio I have ever read!)

Comment by Pradyumna S. Upadrashta on February 27, 2015 at 12:07pm

I have to qualify your statement that technical skill is somehow not important.  

When we say that often the best data scientists are not the most technical, keep in mind the comparison pool -- you're referring to *other* data scientists.  Compared with the general population, they had better be in the top 5-10% in terms of technical skill in general to keep up.  This is not a trivial level of skill, and requires deep knowledge, years of patient study, and experience.  That said, to be the best, often communication and leadership ability are critical.  

One important thing not mentioned here is Confidence.  As a data scientist you are going to be presenting (deeply) technical information to non technical audiences (in some cases) and technical audiences (in other cases) with a solid understanding of technical caveats, nuances, etc. and you should be able to not just be contrarian in thought, but in your ability to convince people who don't necessarily see your point of view, who may be more senior to you, or who may throw technical questions at you (e.g., customers, their engineering groups, etc.) regarding the work you have done. If you have contrarian ideas, but cannot convince others, or be bold enough to take a stand against the group, you will cave to group think.

That said, yes, absolutely, women can be terrific Data Scientists.

Comment by HUI LIU on February 27, 2015 at 11:22am

Great topic. I would love to believe all three are facts, but I doubt about the first one. I don't think women is more of a contrarian thinker than the counterpart. Being a women myself, I feel that women needs to improve their contrarian thinking or to be more brave to express their opinions or challenge the authorities. I also disagree that "the best data scientists do not have the strongest technical skills". Being a statistician for many years and want to become a data scientist, I have found that improving technical skills is the biggest challenge.  I worked with people who are excellent at communication and team work but simply is not qualified. I really doubt they love to play with data or spot trends without strong technical skills. They do not even know where and how to start. I have seen people making excuse that "Oh I have not programmed myself for a while..." I really admire data scientist who are excellent in technical skills as well as communication skills and I think people needs to know what they are doing before communicating with others. 

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