Attending the Women in Data conference – Claire Shadbolt

Data has become commonplace in everyday life; the current landscape is rich with opportunities to capture, analyse and interpret data. Thus, data scientists are in tremendous demand, and this will only continue to increase. As someone who has just started their career in data as a Data Scientist Intern at LIDA, I wanted to attend a conference where I could discuss and learn more about the current data science landscape and its opportunities for women. With a quick online search, I came across the Women in Data organisation (WiD for short). WiD focuses on encouraging diversity in data to help create a representative workforce. Since 2015, their annual conference has encouraged women to network and share their experiences of working in data. The premise of the 28th November conference was very enticing: a day filled with talks from inspirational women, as well as the opportunity to attend a number of different computer programming workshops.

On the empowerment stage, the day was kicked off by the WiD UK co-founders Roisin McCarthy and Rachel Keane. As recruiters, they have noticed a worrying trend that fewer women are applying for data science roles across all levels each year. In 2000, there was a 50/50 split between male and female workers in the UK data field. Whereas, in 2019 the percentage of female employees in data has decreased to 27%.

I started out in academia with an undergraduate degree in Natural Sciences here at the University of Leeds, which included a year studying abroad in Australia. I say “studying”, but a large part of that year was spent exploring the idyllic setting of the country! It also presented a fantastic opportunity to participate in computer science, economics and environmental sciences modules that were not offered as part of my Leeds degree. These modules, along with the endless amounts of climate change documentaries I found myself fixating on, led me to pursue a Masters degree in Climate Change and Environmental Policy. The degree encompassed the economic, social and physical aspects of climate change, and if a module involved any data analysis, I found I was immediately engrossed. I find it fascinating that the development of new techniques can support policy-makers to make more accurate and informed decisions, that otherwise might not be possible. As a result, the internship at LIDA was really appealing as I could develop my computer programming knowledge using real-world data. It also presented the opportunity to work in an interdisciplinary arena with training opportunities for different software packages like Tableau and GIS, which are new skills I want to learn.

At the WiD conference, Baroness Kate Rock explained that it is essential to have a diverse workforce, in terms of gender, ethnic and socio-economic backgrounds, to tackle bias in algorithms. The app Safe and the City, developed by one of the speakers, Jillian Kowalchuk, addresses this problem specifically. To get from A to B Google maps calculates the quickest route possible. However, this does not take into consideration the safety of the journey. For example, has someone experienced harassment or felt vulnerable during that journey? Partnered with UN Women UK, Jillian developed the app Safe and the City to increase awareness and knowledge for people to travel where they want with safety concerns in mind. The app allows users to share and input their own data, which provides a sustainable safeguarding solution to ensure proper representation of safety needs when travelling. It was a very compelling talk, particularly noting the positive impact that solutions to representation issues can have for different communities.

My own project with Dr Ian Philips aims to identify areas where different policies and technologies can have the greatest impact on CO2 emissions reductions in the transport sector. This is an important spatial solution to climate change in the UK because current transport policies are nowhere near sufficient in dealing with the substantial volume of greenhouse gas emissions produced in the transport sector. My project also considers the social vulnerabilities that might occur through reduction initiatives. By executing an individual and a household level microsimulation, I will develop small area spatial indicators of capabilities and vulnerabilities to transport decarbonisation technologies and policies. These will, in turn, provide urgently needed insights for policymakers aiming to identify equitable, non-biased solutions for specific locations that don’t risk marginalising vulnerable members of society for whom more environmentally friendly transport alternatives to car travel, e.g. cycling, are not possible.

Solutions to the problem of the decline of women in data roles also have to understand the possible underlying reasons. Another topic of discussion at the WiD Conference was the importance of examining the barriers that prevent women from starting a career in data. According to an OECD survey, conducted with 15-year-old UK students, girls typically feel discouraged when it comes to pursuing STEM subjects. Exposure to female role models in data science at a young age combats this by instilling self-belief and greater confidence for girls in STEM subjects. Not-for-profit organisations, like Code First: Girls, offer free training to young women across the UK to increase the number of women in tech. Creating a supportive network and visible data mentors can have a positive impact on girls’ perceptions of STEM subjects, for example having a STEM role model results in a 12% increase in interest of STEM subjects. Therefore, girls with a role model can imagine a future career in STEM. A gender-diverse workforce improves dynamics and productivity within a team, as the gender mix can offer an assortment of knowledge and skills.

When I started my LIDA internship, I was very pleased to see that I would be working in such a diverse environment. We interns come from different academic backgrounds and have different skills sets. If one of us has a data or coding problem, we can quickly troubleshoot ideas and this offers us a broader range of solutions. Diversity in the workplace is a great benefit.

Listening to the speakers and chatting with the other delegates at the conference, I found the stories of women in data inspiring. It was a valuable experience. I will take what I learnt from the conference and apply it to my working life. If everyone is properly represented during the problem-structuring and the data analysis process, it ensures equitable solutions and outcomes in data and AI overall. Also, to bridge the gender gap in data, I aim to seek out volunteering opportunities in schools, or with the Council, to encourage girls to develop and enhance their coding skills. Hopefully, they might begin to enjoy coding as much as I do.