During her time at UCL, Bunmi embraced a dynamic and interdisciplinary approach to learning, combining her passion for engineering with interests in philosophy, dance, and creative technology. She highlights how the university’s environment encouraged her to explore diverse opportunities, develop strong analytical skills, and build a foundation in mathematics, statistics, and machine learning - key elements that have shaped her career.
Can you tell us what drew you to study Electronic and Electrical Engineering at UCL and how that decision has shaped your career?
For as long as I can remember, I have been passionate about building things. When I discovered this was what engineers did, I knew that was the path I wanted to pursue. When it came time to choose a specific engineering discipline, I was influenced by my sister, who was studying Electronic and Electrical Engineering. My interpretation of her degree was that it provided an understanding of the mechanics behind rapidly evolving technologies such as phones and computers, which fascinated me. This curiosity drove my eagerness to study the course myself. When selecting a university, I was drawn to institutions that valued both technical excellence and social progress. UCL stood out to me, particularly after learning about its rich history - being the first university in the UK to admit women and its longstanding contributions to social, philosophical, and technological advancements. These values align with my own, making UCL the ideal place for my studies.
What were some of the key skills or experiences you gained during your BEng at UCL that you still use in your current role as a Data Scientist?
One of the most valuable skills gained from an engineering degree is analytical thinking, which remains useful long after graduation. It’s a skill I continue to apply in every role I’ve taken on throughout my career. On a more technical level, many of the mathematical concepts I learned during my studies are still relevant and actively used in my work today.
Your career has spanned roles in software engineering, applied machine learning, and data science. How did your time at UCL prepare you for such a dynamic trajectory?
The environment at UCL taught me to be dynamic and open to new experiences. There is something about the university that makes you feel like you can do anything - you’re not confined to a single path. You can study engineering while also exploring philosophy, joining a cheerleading team, or performing in a dance troupe. This sense of freedom and flexibility encouraged me to embrace diverse interests and opportunities.
Looking back, were there any specific projects, modules, or professors at UCL that had a significant impact on your career journey?
During my time at UCL, many lecturers inspired me, including Sally Day, Ioannis Papakonstantinou, Polina Bayvel, and Nadia Berthouze, to name a few. In terms of coursework, my modules in mathematics, statistics, computer science, and machine learning have been particularly relevant throughout my career.
Beyond coursework, one project that had a significant impact on me - aside from my dissertation during my Master’s in convolutional neural networks for video classification - was an engineering half-term project. The exact name escapes me, but the concept was simple yet powerful: We were given a problem statement, had a week to form a team, develop a solution, and present it. This experience provided valuable insight into real-world problem-solving and teamwork, mirroring the collaborative nature of the workforce.
You’ve achieved a lot since graduating, including a Master’s degree in Data Science at UCL. What motivated you to pursue further studies, and how has it benefited your career?
As I mentioned earlier, I have always been passionate about building things. Over time, my interests evolved from robotics to software engineering and ten to exploring how mathematics could be used to model intelligence. This curiosity led me to develop a deep fascination with artificial intelligence and machine learning, ultimately inspiring me to pursue a degree in data science.
You’re currently working as a Vice President in Applied Machine Learning at J.P. Morgan. Could you share a bit about what your role involves and what excites you most about it?
In my role, I work with businesses within the firm to help them leverage machine learning and AI. Beyond the work itself, which I find enjoyable, fascinating, and challenging, I truly appreciate collaborating with my colleagues. I learn so much from them daily, making my job even more rewarding.
You’ve also taken on a role as an Associate Lecturer at the University of the Arts London. What inspired you to explore teaching, and how has the experience been so far?
Another passion of mine is creativity - specifically, exploring how technology can be used in art to create new experiences. In my spare time, I work on projects in this space, particularly in my practice, where I build immersive theatre experiences. Digital art is a deep passion of mine, and as the field continues to evolve, I wanted to share what I’ve learned so far. This desire to contribute and inspire others ultimately led me to lecture.
As someone who has benefited from mentoring, such as the Google Top Black Talent programme, how important has mentorship been in your journey, and what advice do you have for students seeking mentorship?
One of the biggest benefits of mentorship in my career has been having a sounding board when navigating different career paths. My advice to anyone seeking mentorship is to not be afraid to reach out - many people are more willing to help than you might expect. The right mentor for you will be the one you connect with the most, so don’t hesitate to start those conversations.
What advice would you give current UCL students or recent graduates who are considering careers in data science, machine learning, or engineering?
My best advice is to keep improving yourself - continuously learning and striving to understand topics beyond the surface level. Take the time to truly grasp concepts on a deeper level. Build projects, experiment, and don’t be afraid to fail. Growth takes time, so enjoy the learning process and pace yourself. The industry is evolving rapidly, and the best way to keep up is to stay curious and always seek new opportunities to learn and explore what’s out there.
We recently saw you at one of our alumni events. Have you stayed in touch with your UCL peers?
I try to attend alumni events whenever I can and still stay in touch with my coursemates. To this day, I even travel with some of them! We also have a group chat for our engineering class where we stay connected, and though meetups are rare, we occasionally manage to organise one.
