About this role
About us
GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday.
We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific.
The role
The Threat & Analytics Lead builds GoCardless's data-driven understanding of fraud and financial crime risk. You'll bring specialist analytical expertise to both domains, helping the business understand emerging threats, measure how well existing controls are working, and identify where prevention and detection need to get stronger. Your evidence and insights will inform our strategy and how we prioritise our investments.
You'll work closely with Product, Engineering, Operations and Data Science to analyse large, complex datasets and surface patterns, trends and risk concentrations across the customer lifecycle, spanning fraud prevention, transaction monitoring, sanctions screening, customer risk management and broader financial crime work. You’ll work hand-in-hand with the teams who own fraud and financial crime strategy, governance, policy and operational delivery.
The Threat & Analytics Lead is a senior-level role with a high level of complexity, autonomy and expectation of impact.
What excites you
• Getting to the root cause of problems — not just reporting what’s happening, but understanding why
• Working with data to uncover patterns that aren’t immediately obvious
• Bringing structure and clarity to complex or ambiguous problems
• Influencing decisions through evidence rather than opinion
• Building analytical frameworks and approaches that improve how we understand fraud and financial crime risk
• Seeing your work directly impact fraud losses, detection and business performance
What excites us
• You have strong analytical capability and are confident working with large datasets using SQL, Python and BI tools.
• You have experience applying statistical and analytical techniques to large datasets to identify patterns, measure performance and assess risk.
• You are able to translate complex data into clear, actionable insights that non-technical stakeholders can understand.
• You are comfortable working across multiple stakeholders and influencing without direct ownership.
• You take ownership of problems, bring structure to ambiguity, and drive work through to completion.
• You are comfortable working toward a high level organisational KPI and independently developing and validating hypotheses to create