Data Scientist (Growth Team)

About this role

We’re Capital on Tap 👋 💳 Capital on Tap started because small businesses were underserved. Big banks were slow, their products weren't fit for purpose, and small business owners often couldn't access what they needed. We set out to fix that. Today we're a financial platform - not just a credit card company. We offer a best-in-class business credit card, SME-focused spend management platform, a savings product that hit £1 billion in funds within its first year, and a growing suite of tools and financial products that make running a small business easier.

1,000+ employees, £20bn in annual card spend, 200,000+ customers, 17,000+ Trustpilot reviews averaging 4.7 stars, and we're profitable. We’ve done a pretty good job so far, but we’re just getting started! 🏢This is a Hybrid role, working from our London (Moorgate) Offices 3 days per week. Growth Team at Capital on Tap You’ll join the Growth Team, reporting to our Head of Growth. The team’s mission is to increase customer acquisition, activation and retention across our book of customers.

What You'll Be Doing Developing and maintaining predictive models that influence our strategy across the entire customer lifecycle; acquisition, activation and retention. Understanding the commercial levers within the growth team and how predictive models help to improve them. Evaluating complex datasets to find hidden opportunities and help us make smarter decisions. Turning complex analysis into simple, compelling stories that get everyone on the same page.

Collaborating with a wide range of stakeholders to ensure seamless implementation of your solutions. Exploring and advising on the latest tools and techniques in data science to help us stay ahead of the curve. We're Looking For Strong analytical and quantitative skills with the ability to translate findings into clear recommendations. 2+ years experience building statistical models in Python and extracting/manipulating data in SQL.

2:1 or higher in a quantitative degree from a top university. Someone who takes ownership of their work, manages their time independently, and uses good judgement to decide what matters. Comfortable working autonomously in a fast-moving environment. Preferred: 2-4 years' experience in top-tier consulting or a high-growth startup. 1st-class degree in a quantitative field from a top university. Understanding of and interest in how to apply a commercial lens to Data Science problems.