binary code, data scientist

By Joanna Hu, Principal Data Scientist, Exabeam

With a growing number of organisations recognising the financial, social and cultural benefits of recruiting more women into data science, isn’t it time to explore the opportunities on offer?

Like many women who graduate with a tech degree, it took me a couple of years to figure out that data science was my niche. Thankfully, I eventually found my way and went on to forge a rewarding career in this exciting field.

With advancements like machine learning and big data now in the frame, I’ve been lucky enough to contribute to discoveries and solve real-world problems in healthcare, energy, and now – as principal data scientist at Exabeam – the cybersecurity industry.

I’m not alone in thinking that data science is a rewarding field to work in. Based on overall job satisfaction scores, the role of data scientist is ranked #7 in the Glassdoor ’25 best jobs in the UK for 2019’ listing – with an average base salary of £46K.

A long heritage

Historically, women have made a significant contribution to the evolution of computer science.  Before the invention of electronic computers, women were more prominent in the computer science field, and contributed a lot to the invention of the first electronic computers.  As well as Joan Clarke, who worked alongside Alan Turing to crack the Enigma cyphers during WW2, the other female codebreakers at Bletchley included Margaret Rock, Mavis Lever and Ruth Briggs.

More recently, there’s been trailblazers like Dame Steve Shirley, who first embarked on a technical career at the prestigious Post Office Research Station in Dollis Hill, where the Colossus codebreaking computers used at Bletchley were created. Founding her own software company in 1962, her team of female freelancers would go on to undertake many cutting-edge projects – including programming the black box flight computer used in Concorde.

Today, a new generation of women are forging their futures within the tech sector. Coming from a diversity of backgrounds, they’re making great strides in the field of data science – and many have done so without an initial background in science, technology, engineering or mathematics (STEM).

A field rich with opportunities

Make no mistake, data scientists are in high demand. A recent study found that 80 per cent of UK businesses are looking to hire a data scientist in 2019, and IBM estimates that by 2020 the demand for data scientists and analysts will leap by 28 per cent.

That said, while women represent 47 per cent of the UK workforce, they only hold around 19 percent of all available tech jobs. Clearly, it’s time to redress the balance.

That’s certainly the opinion of bodies like the Alan Turing Institute and organisations like the International Women’s Day (IWD) movement. Indeed, the IWD #BalanceforBetter 2019 campaign is making great strides in changing hearts and minds – by showcasing how women in tech are achieving impressive outcomes for themselves and others.

The good news is a growing number of companies now acknowledge there are significant gains to be won by addressing the issue of gender inequality in their tech workforces. As a result, they’re eager to hire more female data scientists. Indeed, Gartner projects that in the next three years, both women and men will equally populate the role of chief data officer (CDO).

Why companies want more women in data jobs

Research organisations like McKinsey have found that highly diverse companies are 15 percent more likely to outperform those that are not gender diverse. Alongside enhanced financial performance, reports by analysts such as Morgan Stanley, McKinsey and Gartner confirm that having more women in the tech workforce creates a more cooperative and collaborative atmosphere.

Their research findings also highlight how women are more aware of risk, which in the field of big data is a major plus. What’s more, women tend to excel at communication, team nurturing and problem-solving—all vital qualities when working in the field of data, where outcomes depend on asking the right questions, and listening to the answers.

Finally, and perhaps most interestingly, the research findings illustrate how women are strong advocates for data-driven decisions and tend to be more solution-oriented than male counterparts.

I’m not a rocket scientist – can I make it in data science?

Absolutely. If you’re a curious person, are passionate about innovation, and have an interest in technology, then this may well be the career for you. Stephanie Glen’s recent blog – charting her life-changing journey from office cleaner to data scientist – highlights that as far as she’s concerned, a love of logic problems is the most important pre-requisite for the job.

Typically, the skill sets required include math, statistics, coding and system design. But, as a recent article in CIO magazine highlights, exacting true business value from data requires a unique combination of skills that includes storytelling and intuition.

Truth is, women with a passion for learning who want to try something new will find there’s a number of big-name tech companies out there that only too ready to help you develop the digital skills you need to embark on a career in data science. Plus, there are organisations like Girl Geeks that are proactively supporting women to enter and progress in the field.

Top tips?

If you’re already working in the tech field, or are ‘data science’ curious, then teach yourself the data science knowledge and network as much as you can.  Before deciding this was the path I wanted to commit to, I spent time talking to people about their work, went on workshops, joined weekend meetups and tried out small projects from the online courses.

These days, there are lots of resources available to women who want to make a go at it in this field. Find out about which new tools you’ll need to learn, then use your free time to hone your skills – pretty soon, you’ll become an expert.

When it comes to seeking out new job opportunities, follow good companies and people rather than high salaries. Ideally, you’ll want to work for companies that have intelligent leaders and care about their female talent. Most importantly, hunt down a great mentor and commit to continuously learning from superiors and peers.

Finally, believe in yourself and, no matter what roadblocks you face on the journey, don’t let anyone limit your potential.

Joanna HuAbout the author

Joanna has rich industrial working experience within data mining and big data analysis for healthcare institutions, energy companies, and retailers. Through her work she aims to help them identify frauds, predict risk and outcome, reduce cost, and estimate product qualities.

Joanna has a Ph.D. from University of California, Berkeley, in Nanotechnology and a Ph.D. from University of Michigan in computational earth sciences. Before joining Exabeam in 2015 as a senior data scientist she worked at Ayasdi as a data scientist building and improving algorithms for client healthcare institutions to produce the best treatments for patients. Since October 2018 Joanna has been principal data scientist at Exabeam.