Dr Janet Bastiman, chief data scientist at Napier, has 20 years of experience pushing the boundaries of data science in telecomms, marketing and the financial sector, helping both start-ups and established businesses implement and improve their AI offering. On this International Day of Women and Girls in Science, we spoke to her about her career in science, the critical role of diversity of thought in workplaces and her advice to women and girls who want to get into the technology space.
Q: Who or what inspired you to make the educational and career choices you have made?
Janet: I am fortunate to have grown up in a household where science and technology were valued and encouraged. My dad, who was a science teacher and my mum who was a computer programmer at the local university, provided me with early exposure to electronic and science kits, and we even had access to BBC and Acorn Electron computers at an early age. This allowed me to explore and discover the world through the lens of technology and science, and instilled in me a love of asking questions and investigating the world around me. My upbringing provided me with the opportunity to delve into the world of exploration and discovery, which has had a big impact on my personal and professional development. I am grateful for the experiences and opportunities that I had early access to and I believe they helped shape my curiosity and passion for science and technology.
Having strong female role models in my life has been incredibly influential in my personal and professional development. My mother, and the long line of independent and powerful women before her, have instilled in me a fierce determination to succeed and break down barriers. Growing up seeing two women rule and run the country, and also seeing women in leadership positions, including my mother and grandmother (who stood for local elections), showed me that women are capable of anything they put their minds to. Furthermore, my secondary school science teacher, Mrs Simmonds, who was the head of the science department, was a strong advocate for girls to pursue careers in science and technology. She ran extra clubs and activities to provide opportunities for girls to explore and discover the world of science and technology, and she never let her gender limit her own potential. Her example and encouragement had a profound impact on me, and I am grateful to have had such a role model in my life.
Q: What changes, if any, have you seen in the opportunities open to women and girls in science over the course of your career?
Janet: There is a growing awareness and support for returning to work, particularly in the past decade. The idea of sharing family responsibilities evenly is becoming normalised. There are also more resources available such as conferences and groups for women in technology, which can help to equip individuals with the skills and experiences needed to return to work after taking time off, something I never felt able to do.
Q: Were there any particular barriers you encountered? If so, how did you get over them?
Janet: In the past, I have had to change jobs when the people in higher positions did not value my contributions and were condescending towards me. Women may be more risk-averse when it comes to their careers, but It's important to be in a place where you feel valued and respected, and if you don't, it's okay to leave.
This "hustle culture" that emphasises working long hours and pushing oneself to the brink of burnout is not sustainable or healthy and should not be encouraged. This is why having a mentor is incredibly valuable, someone who has had similar experiences and can provide clear insight and guidance to navigate your career. Having a good mentor who knows where to go, what to do, and what will help you achieve your goals can make a significant difference in one's professional journey.
Q: As Napier's chief data scientist, what impact do you think new technologies like AI and ML will have on the future of financial crime compliance? How do you approach incorporating human oversight and decision-making into the AI financial crime compliance process?
Janet: Incorporating human oversight and decision-making into the AI financial crime compliance process is crucial to ensure ethics are considered. This includes understanding the potential impact on diverse populations and considering alternative approaches to ensure accuracy and fairness. It's important to have a diverse team in place to fully understand and address these issues, and to build trust in the technology. It's also critical to consider the implications and impacts of any errors. Full understanding comes with empathy and being open to working with people from different backgrounds.
When focusing solely on building a product for a specific outcome, it's easy to overlook the potential impact of AI on people. For example, the risk profile of a single mum with multiple jobs could overlap with that of a money launderer, but investigating her or freezing her account because of this confusion could have a catastrophic effect on her. Considering alternatives and reframing the approach so that the business can understand the potential implications means less likelihood of privacy breaches or backlashes. Varied datasets can help ensure accuracy and inclusion of marginalised groups. When the algorithms used to train the system are not sufficiently diverse, inaccuracies and unfairness in identifying individuals creep in. This can disproportionately affect marginalised groups, such as people of colour and women. While working on a project, it's essential to consider the intended outcome and potential ways in which it could go wrong. Data scientists should take an extra step to consider the implications and consequences of any inaccuracies to ensure that the outcomes are accurate, trustworthy and fair.
Having empathy for those who may be affected by financial crimes is key to understanding that there is always someone paying the cost and suffering while scammers pocket the money. Our role is to provide the technology to stop these individuals and help protect people's financial well-being.
Q: Can you discuss any steps your team takes to promote diversity and inclusion in the workplace?
Janet: I’ve found that hiring people from varied backgrounds delivers better and smarter solutions. Diversity of thought brings different perspectives on how to tackle challenges, engage customers, develop products or services, solve problems and more. A diverse group of people allows for various viewpoints to be considered when making decisions or coming up with solutions. This not only leads to better decision making but can also bring in fresh ideas and approaches that would otherwise not be explored.
Another major benefit is increased innovation, as different backgrounds bring different skillsets which can be leveraged in times of need. The team is therefore able to think outside the box and come up with creative solutions that may have been overlooked before. The ability to foster scientific curiosity and overcome inherent biases is a trait that can be difficult to teach, but is greatly enhanced by a diverse workforce.
Accepting that people have lives outside of work and giving them the flexibility to add time in their calendar for a school meeting, lunch or a dentist appointment is essential to inclusion in the workplace. Accommodating schedules and offering flexible work arrangements means that people with a variety of responsibilities and experiences can have a data career.
Q: What would be your advice to women and girls who want to follow in your footsteps?
Janet: My advice to young girls is to follow their passions and not be limited by societal expectations or gender stereotypes. There are countless career paths available, and it's important to pursue the ones that truly interest you, regardless of whether they are typically considered "pink" or "for girls."
It's important to not let anyone tell you that you can't do something. Your perspective is invaluable, and you will find a unique way of approaching and solving problems.
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Photo by Milad Fakurian on Unsplash
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