About the Role
Data sits at the core of our mission at GoCardless. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention.
As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network.
At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale.
What you’ll do
- Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development.
- Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions.
- Shape the strategic roadmap for the Payment Intelligence space, translating complex data challenges into actionable, high-impact goals.
- Drive cross-functional impact by working closely across disciplines to build end-to-end technical solutions, from concept to production.
- Influence Senior Leadership by acting as the bridge between technical complexity and business value, communicating ML strategy to senior stakeholders.
What excites you
- Driving cutting-edge advancements in Data, AI, and Machine Learning within the payments space with a multidisciplinary team.
- Mentoring a high-performing team and fostering a culture of technical excellence.
- Solving the complex, real-time challenges of fraud prevention and payment optimisation at scale.
- Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.
What excites us (Requirements)
- 2+ years managing Data Scientists within complex, high-stakes domains.
- A hands-on leader comfortable diving into the codebase. You bring strong expertise in Python and SQL to oversee the full lifecycle of a model, from initial prototype to robust production deployment.
- A decisive collaborator who can navigate technical trade-offs and translate complex ML concepts for cross-functional stakeholders and leadership.
- Familiarity with complex data environments and model architectures, such as deep learning (experience in Fintech, Fraud Prevention, or Payments is a big plus).