About the Role
Fraud prevention is an ever-evolving puzzle, making it one of the most rewarding and impactful areas in fintech. At GoCardless, our Fraud Prevention team develops the intelligent systems that protect our platform, our merchants, and their customers.
As a Senior Data Scientist, you will guide the design and delivery of models that operate in real time across our global payment network. You’ll work at the intersection of machine learning, graph-based detection, and behavioural modelling to stay ahead of changing patterns turning research into production systems that make a tangible difference in the fight against financial crime.
You’ll collaborate closely with Engineers, Fraud Analysts, and Product Managers to help shape the technical roadmap as we expand into new markets. Our stack is centred around Google Cloud Platform and Vertex AI, using Python, SQL, and BigQuery to build and support high-performance models at scale.
What you'll do
- Contribute to the full model lifecycle, from initial discovery and feature engineering through to production, experimentation, and continuous monitoring.
- Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers.
- Foster a responsive feedback loop, adapting models as patterns evolve to ensure our defences remain robust and effective.
- Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally.
- Support the team’s growth through technical mentorship, knowledge sharing, and a commitment to high-quality code.
What excites you
- Solving complex, dynamic problems: Developing systems that can adapt and respond to changing environments.
- End-to-end ownership: Seeing a project through from a conceptual business need to a live, impactful solution.
- Strategic influence: Contributing to the ML roadmap and helping determine what we build next, rather than just how we build it.
- Holistic Data Science: Engaging in deep-dive analysis, prototyping, and live experimentation.
- Modern Infrastructure: Building production-grade models on GCP and Vertex AI, with the flexibility to explore advanced architectures.
What excites us (Requirements)
- You hold a degree (or PhD) in a STEM discipline, or bring equivalent depth through commercial experience.
- You have hands-on experience with modelling approaches such as deep learning, graph-based methods, or sequence models. While fintech experience is great, we value transferable skills from fields like cybersecurity or risk modelling.
- You have a track record of deploying models in production that create measurable value.
- You can translate complex ML concepts into clear, practical solutions for stakeholders across the business.
- You enjoy writing clean code and helping the team thrive through thoughtful reviews and shared learning.