About the job
About GoCardless
GoCardless is a pioneering global bank payment platform that empowers over 100,000 businesses, ranging from innovative startups to established brands, to seamlessly collect and send payments through direct debit, real-time payments, and open banking.
With an impressive annual processing volume exceeding US$130bn across more than 30 countries, we facilitate both recurring and one-off payments, alleviating the burdens of follow-ups, stress, and high fees. Our AI-driven solutions enhance payment success rates and minimize fraud risks. Additionally, our open banking integration with over 2,500 banks enables our customers to make faster and more informed financial decisions.
Headquartered in the UK, with offices in London and Leeds, we also have a presence in Australia, France, Ireland, Latvia, Portugal, and the United States.
At GoCardless, we prioritize support and are dedicated to making our hiring process inclusive and accessible. If you require any adjustments or additional support, please reach out to your Talent Partner — we are here to assist you!
Remember, we do not expect you to meet every single requirement. If you are enthusiastic about this role, we encourage you to apply!
The Role
Data is at the heart of our mission. We utilize bank account information to deliver intelligent payment solutions, enhancing payment success rates and preventing payer fraud.
As a Senior Data Scientist in our Payment Intelligence team, you will collaborate with Software Engineers, Product Managers, and Designers to transform innovative concepts into reality. You will be responsible for the complete lifecycle of our algorithms, from the initial idea to the production-ready code that drives our global payment network.
Our tech stack is centered around Google Cloud Platform and Vertex AI, creating a high-performance environment for innovation. Our Data Scientists work at the intersection of Python, SQL, and BigQuery to develop and deploy high-performance models at scale.
Key Responsibilities
- Lead the comprehensive delivery of models at scale, from initial discovery and feature engineering to production, A/B testing, and ongoing monitoring.
- Collaborate with cross-functional teams to design and implement advanced data-driven solutions.

