I had never given too much thought to the gender balance within my team; we all get along so well that it has never been a cause for concern.
Recently, however, the issue of the male-female split within data science has become more pressing for me. I work in the same office as The Female Lead, an organisation founded by my company Starcount’s CEO, Edwina Dunn, and designed to make a diverse range of women’s stories more visible. The Female Lead are on the brink of launching 20 in Data & Tech 2018, a series of photos and filmed interviews with 20 remarkable women in these industries.
Having had discussions with The Female Lead team about the need for this project and the process of identifying and highlighting female achievement in data and technology, it prompted me to ask the inevitable questions: why aren’t there more women in data science? Why is it still so hard to find girls who want a role in the data industry?
Ultimately, why aren’t we showing girls and young women that there has never been a better time to be a woman in data?
Being a data scientist myself, efficiency is part of my DNA. Not wanting to duplicate or simply echo what the internet already has to offer, I did my research before writing this article.
If you google the answer to ‘Why there has never been a better time to be a woman in data’, a vast number of articles immediately pop up referencing the ever-increasing reasons it’s fantastic to be a woman in today’s society. However, not one of these articles specifically references the fantastic opportunities data science offers women, nor why it’s so important to have an equal playing field in this industry.
1. It’s logic plus creativity
One of the most satisfying parts of my job is the wonderful blend of logic and creativity data science offers. There will always be an answer to a particular question, but it’s up to you to go and find it. You can go into as much or as little depth as you like – test the newest, most sophisticated machine learning algorithm, or rely on simple and trustworthy stats to solve the problem. Prove it, disprove it, visualise it, create the best story you can – it’s storytelling, within the boundaries of logic!
2. Data science is far more than science.
Once you get into data science, it really is a door opener to learning how an entire business operates. You’ll be exposed to the entire spectrum of business development and transformation; hearing the client’s business problems, coming up with a method for solving them, selling the solution, proving the value, providing the juicy data science in the middle, presenting it back, taking on feedback and suggesting more work that can be done.
3. You can try before you buy
There are SO many free resources on the internet now – pick any discipline and any technique, whether you’re an established pro or need a complete beginner’s guide. You can quickly tell if you’re going to like coding and enjoy the challenge of answering business problems using maths and science, at little-to-no cost. This is not a luxury you have in many other professions, where you don’t until you try.
4. A range of people means a range of customers…
…and clients! Companies that are striving to ‘put the customer first’ are relying increasingly on sophisticated data science to solve this objective. A diverse data science team, by definition, will contain a range of different customer types, making the company as a whole better equipped to understand business objectives from any customer’s point of view.
My teammate recently asked me ‘How do you spell makeup?’, while performing a segmentation for a retailer. Understandably he does not fit into this type of shopper. I, however, am a makeup lover and a big fan of beauty tutorials, meaning I not only know the most common spelling of makeup, but also understand the consumer mindset being analysed by my colleague. The intricacies that he saw as anomalies were meaningful to me. Certain patterns made perfect sense to my eye. My specific experience and knowledge brought a new level of understanding to the data.
On the other hand, I recently had to pass on a pet-centric project, as, contrary to the stereotype of girls loving cute, fluffy animals, I have much less knowledge of the topic compared to the boys in my team.
By virtue of having a more diverse data science team, your company will be able to provide effective and relevant solutions to a far broader range of clients.
5. People will remember you.
As a woman in data, it really is your time to shine. In a team where the majority of data scientists will still – unfortunately – be male, people will remember you.
It won’t be easy; you will still have to prove yourself, work hard and gain the respect of your colleagues, but there will always be that something, inherent to your nature, that will make you memorable.
Hannah Poskett is an Observatory Scientist at Starcount.