Catherine’s Journey at Lendable: From Individual Contributor to Leading a Team of 15

What has your journey at Lendable looked like so far?

I’m currently the Head of Data Science at Lendable. My journey here began three years ago, when I joined as a Lead Data Scientist working on credit risk models for our UK credit card product. That first year as an individual contributor was incredibly fulfilling – being able to see my models go into production and drive real commercial and customer impact was the kind of reward you dream of as a data scientist.

Thanks to Lendable’s rapid growth, an opportunity opened up when my former manager moved into a new role, allowing me to step up and lead the Data Science team. Over the past two years, it’s been the most exciting phase of my career:

• Developing data science roadmaps
• Overseeing model launches across all our products
• Supporting UK growth and international expansion (including the US, with more to come)
• Researching new data sources and ML use cases
• Growing the team from 7 to 15 people (and yes, we’re still hiring!)
• Designing our career progression framework

What makes you, you?

I’m good with numbers.

Yes, it might sound a bit nerdy, but numbers stick with me. I remember data points better than anecdotes. To me, data science is equal parts art and science. I love crafting meaningful stories through data just as much as working with the numbers themselves.

I’m a people person.

The part of my job I cherish most is empowering people to grow. I find joy in building high-performing teams, where everyone has ownership, autonomy, and comes to work feeling energised because they care.

I value balance.

I’m very family-oriented and love spending time in nature. A typical weekend includes walks through parks or forests, cooking great meals, or baking with my family.

What does the Data Science team at Lendable do?

Our mission is simple but ambitious: build better machine learning models, faster, with robust governance and infrastructure.

We work in small, flat-structured teams. Roughly:

• Two-thirds of us are product-facing data scientists developing ML models for UK and US products.
• One-third are ML engineers who build and maintain our decisioning infrastructure.

This setup is relatively unique. At most companies, infra is handled by separate teams, which often slows things down. At Lendable, our end-to-end ownership enables us to move fast.

We’re laser-focused on business and customer impact. Each data scientist owns their models from design to deployment and monitoring. Beyond modelling, we also explore how LLMs and automation can increase operational efficiency.

And above all: we’re a curious bunch. Great data science starts with asking the right questions and uncovering where we can drive real impact.

What advice do you have on career progression?

Start with curiosity, and be patient with the journey.

It’s important to ask yourself what you want to do in the medium to long term. That clarity doesn’t come overnight - it took me five years of career exploration before I realised what I really wanted: to build ML models in a tech-led company.

Once I found that path, my engagement and fulfilment soared. When you're working on something you want to do, your motivation and the quality of your work naturally follow.

Career growth isn’t linear and that’s okay.

Looking over a 10+ year span, my career trajectory has been more like "up → flat → up again." Others might go "up → down → up more." There’s no one right shape.

During my first 8 years at GE Capital, I followed a steady upward path. Then I entered a "critical exploration phase" - 5 years of trying different roles across banks, consultancies, and fintechs. I even took a part-time job at a startup to better understand what environments suit me. It was through this trial and error that I learned about my strengths, preferences, and limits.

When I joined Lendable, everything clicked. I found the environment and challenges I’d been searching for, and I’ve thrived here since.

Personalised development is key.

At Lendable, I strongly believe in tailored growth plans that align individual ambition with business needs. That’s why I created our career progression framework within the Data Science team - to give managers the structure they need to hold meaningful development conversations and support their team’s continued growth.