What did you study at A-level and why did you select those subjects?
I studied Maths, Accounts, Commerce, and Biology. At the time, I was aiming for a career in finance. I didn’t fully understand what life would bring, but I knew I wanted to work in a corporate space—probably in a bank. I loved the idea of wearing smart office clothes, shiny shoes, and sending emails. It just looked like the perfect professional life to me as a young girl.
What degree did you study?
I have a BSc in Accounting, an MBA, and an MSc in Data Science and Artificial Intelligence.
What inspired you to choose and study your degree subject?
As I mentioned, I was drawn to the corporate world and had done well in Accounting during A-levels, so it made sense to study it at university. I studied Accounting and worked as an accountant for about seven years. During that time, I also completed my MBA.
While working, I interacted with data analysts, data scientists, and IT teams. I was always curious about how they seemed to have answers to complex business questions. As someone who already worked with numbers, I started thinking: what if I could also understand and use data in deeper ways?
That curiosity grew. I became more interested in automation and how machine learning models work. I began taking beginner courses on Udemy and Coursera, sometimes applying for fee waivers to access them. The more I learned, the more I wanted to go further. That’s when I applied to the University of Liverpool to study Data Science and AI. I graduated with distinction. And honestly, everything changed from there.
What key skills did you learn at university?
I picked up a mix of technical and soft skills:
- Programming and database work
- Statistical analysis and data cleaning
- Machine learning basics
- Data visualisation and presentation
- Project management and teamwork
- Strong communication and problem-solving
- Big data tools—and, most of all, the habit of continuous learning
What jobs have you had during your career?
- Accountant
- Data scientist
- Data analyst
What is your current job and what do you enjoy about it?
I work as both a Data Analyst and a Data Scientist at an energy broker company. As a Data Analyst, I spend time digging into trends and uncovering insights that help with day-to-day business decisions. On the Data Science side, I build predictive models, like forecasting future revenue or energy usage patterns.
The role is flexible, and no two days feel the same. I like that I get to solve real problems with data and then see how those insights shape decisions. It’s rewarding to know the work I do actually gets used.
Do you have an area of expertise?
Yes. Having worked in two energy-focused companies, I focus on energy use and consumption, especially how better data can support a greener environment. My MSc placement project involved predicting energy load growth in line with the UK's net-zero goals.
What has been your most exciting project?
Building a predictive model that forecasts future network loads with 98% accuracy for the UK’s net-zero initiative.
What are your top tips for working in your industry?
Stay consistent and keep learning—tech moves fast, and there's always something new around the corner, especially with AI and tools. Try to keep up, but also take each day as it comes. And while you're at it, don’t forget to enjoy life too. Having balance helps you stay sharp.
Any advice you’d like to share?
Little drops of water make the ocean. Consistency matters. If you do nothing, nothing changes—but steady effort adds up.
Why are you passionate about your career?
Tech changes every day, which can feel overwhelming, but it also makes the field exciting. I love finding faster, more efficient ways to do things—and AI’s possibilities amaze me.
Keep up to date with Cynthia on LinkedIn.