Cleo

Cleo is a fintech unicorn — an AI-powered financial assistant used by millions. I joined as the youngest hire out of university and rotated through five squads in 14 months.

What I did

Savings Squad — Front-end. Stabilised existing code and prepared the codebase for new features.

Debt Squad — Back-end. Feature lead and tech lead simultaneously. Took a lot of initiative. Gave internal talks on using AI in the workplace and on Cleo's "Learn at Speed" value — was commended for it.

Notifications Squad — Transition into ML. Built a multi-armed bandit for notification send-time optimisation. Learned data science fast: ran experiments, then engineered the production implementation.

UFU (User Financial Understanding) — Core ML work. Used LLMs to categorise and understand millions of transactions. If you can't understand the transactions, you can't provide insights or lend money. This was foundational to Cleo's product.

Hiring — Helped scale the ML engineering team. Conducted ~20 interviews across levels. Built onboarding documentation for new hires.