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In this exclusive interview, we sat down with Damilola Aminat Ahmadu, a self-taught data scientist who went from kitchen to code, showing the world that no background is too unconventional to make an impact in tech.
Damilola, your journey into data science is far from traditional. Can you walk us through how it all began?
It honestly started with curiosity. I was a Chef by profession, juggling part-time jobs to make ends meet in Lagos. But I always had an interest in solving problems and making sense of things. I stumbled upon data science online and was immediately drawn to the idea of using data to tell stories and drive change. It felt powerful. From there, I started teaching myself everything, Python, statistics, Excel, and tools like Google Colab. I had no mentor at the time, just a strong drive and a lot of late nights.
What were some of the biggest challenges you faced transitioning into tech from a non-technical background?
Imposter syndrome was real. I wasn’t coming from a computer science degree or any “tech” job, so I constantly questioned if I belonged. Also, understanding the foundational math behind machine learning was tough at first. But I broke it down into small learning goals and leaned heavily on YouTube tutorials, free courses, and community groups. Another challenge was access to fast internet, a decent laptop, and even quiet time to focus weren’t always guaranteed.
Despite those challenges, you’ve now worked on major projects. Can you tell us about some of your impactful work?
Absolutely. I have had the opportunity to work on data projects in healthcare, government, and fintech. One project involved building a machine learning model to help predict high-risk health cases in underserved communities, which could help NGOs better allocate resources. I’ve also helped public administration bodies use dashboards to visualize service gaps, and even worked on improving fraud detection for financial platforms. Each of those experiences reinforced my belief in the power of data to drive meaningful change.
You have also become a strong advocate for women in tech. Why is that important to you?
Because representation matters. When I started, I didn’t see many women who looked like me in data science especially not Nigerian women with non-traditional backgrounds. I want to change that. I speak at local expos and mentor younger women because I know how isolating it can feel in this field. If I can help just one girl realize she doesn’t need to have it all figured out before she begins, then it’s worth it.
What advice would you give to anyone especially women looking to break into data science from a non-technical background?
Start where you are. You don’t need to know everything; you just need the courage to begin. Be consistent, find a learning path that works for you, and don’t be afraid to ask questions or make mistakes. Also, find a community whether online or offline. Learning in isolation is harder than learning together. And finally, believe in your story. Your background is your superpower.
What’s next for you? Any big dreams on the horizon?
I want to continue working on AI projects that serve Africa’s most urgent problems from public health to governance. I also hope to launch a data mentorship platform specifically for women in underserved communities. Long term, I’d love to contribute to policy-making where data and technology can be better integrated into Nigeria’s public systems. There’s still so much to do and I’m just getting started.
Conclusion:
From working multiple part – time jobs to data scientist, Damilola’s story is a powerful reminder that the future of tech in Africa is not limited by background, but powered by purpose. Her journey is one of grit, growth, and giving back and she’s just beginning to leave her mark.
