Subscribe to DSC Newsletter

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.  


Views: 11268


You need to be a member of Data Science Central to add comments!

Join Data Science Central

Comment by Stephanie Wilson on March 27, 2017 at 8:15am

I agree with Barbara and Antoine - some women are contrarians, communicators, team players, just like some men are, and some are not. This makes sweeping generalizations and stereotypes about women. As a young woman trying to enter in the field of data science, I also found this irrelevant and discouraging. Let's focus on how we can remove biases to allow women to learn the skills they need to become data scientists, not reinforce those biases.

Comment by Barbara McGillivray on August 21, 2015 at 3:22am

I agree with Antoine's comment (apart from the note about "anatomical specificities" which is irrelevant here).

So, is the author saying that if Data Science were more technical, then it wouldn't be a good career path for women? Before reading this, I didn't believe someone would actually write such things in 2015.

I am a women and a data scientist, and I find this article offensive and misleading. It also tries to answer an irrelevant question. Gender doesn't matter for professional abilities, as Antoine says.

If this article intended to encourage women to consider becoming data scientists, it totally failed. It's not by reinforcing sexist stereotypes that we can hope to make the gender gap in technology and science smaller.

Comment by Antoine Dinimant on July 22, 2015 at 12:32pm

Let me just summarize :

  1. Women make great data scientists because they are contrarian
  2. ... and because they are good at talking a lot
  3. ... and because they are good at supporting real leaders
  4. ... and because technical skills are not so important!

Oh, my gosh, these women are good girls! Even when they're a bit contrarian, it's a constructive challenge.

OK, stop kidding. From the title, I had hoped it was just reverse discrimination, but, I'm sorry, this is just plain sexism, the usual clichés hardly disguised into a patronizing welcome.

Please. Women are just regular people. They may have interesting anatomical specificities, but I'm afraid this is far from data science.

'Why women make great data scientists?' sounds like 'why Black men are so good at basketball?' or 'why Jews make wonderful bankers?'.This question is just bias and nonsense. You just have to accept that sex or gender are not relevant criteria for professional abilities.

I'd like to raise another question : 'how comes that a data scientist is so illiterate in social analysis that he cannot tell sexism from a saucepan when he's hitting himself with it?' I've just been told that data scientists 'turn data into information - information into knowledge and insights - and valuable, actionable insights into better decision-making'. Oh my gosh !

Comment by Sierra Martin on March 30, 2015 at 6:59am

good read. 

Comment by Lőrinc Nyitrai on March 29, 2015 at 8:17am
As long as social impact is magnitudes higher than neurological differences, this topic remains offensively sexist for my taste.
Comment by Savita Kirpalani on March 25, 2015 at 9:23am

Very well said Micheal...including all the points you mentioned, an eye for detail is very important for succeeding as a data scientist. Most all women I have interacted with, look at both,the fine print and the data granularity.

Comment by John Doe on March 5, 2015 at 11:31am

I believe the author is the from the Data Science Association,, an organization that has recommended a code of conduct for all data science. As such I would like Mr. Walker to comment on the following submitted to his organization's blog last year. In it Mr. Malak, the vice president, suggests that women are bad at spatial relations.

Comment by John Doe on March 5, 2015 at 11:24am

Comment by Pradyumna S. Upadrashta on March 5, 2015 at 8:43am

Sione Palu: All choices are driven by incentives; If women are not applying to STEM programs, it is because they don't see an incentive, as opposed to being unable to succeed.  Plenty of women in India, for instance, pursue advanced degrees and go on to successful careers in STEM fields, and have done so for many decades.  For whatever reason, the entire class of Chemical Engineering graduates that followed my own, was comprised of mostly women, at one of the top Chemical Engineering schools in the US.  So, things have perhaps already changed, but to see the effects of that change will take at least a decade due to the natural lag between perception (historical) and reality (current).  I would even suggest that people (/media) are reacting to a scenario that no longer exists, and that within 10-20 years we will see a tremendous difference in the demographics as these graduates become more visible.  Media and public perception always lag behind reality, which means we will more than likely overshoot.  I think Carenne Ludena is spot on.

Comment by Andres Fortino on March 5, 2015 at 8:43am

Yeah, just take a respected and brilliant statistician of her time:  Florence Nightingale!

Follow Us


  • Add Videos
  • View All


© 2017   Data Science Central   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service