Description
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.
Key Responsibilities
- 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
Requirements
- Strong analytical capability and confidence working with large datasets using SQL, Python, and BI tools
- Experience applying statistical and analytical techniques to large datasets to identify patterns, measure performance, and assess risk
- Ability to translate complex data into clear, actionable insights that non-technical stakeholders can understand
- Comfortable working across multiple stakeholders and influencing without direct ownership
- Taking ownership of problems, bringing structure to ambiguity, and driving work through to completion
- Comfortable working toward a high-level organisational KPI and independently developing and validating hypotheses to create impact
Nice to Have
- Experience analysing fraud or financial crime data in payments, fintech, or financial services industries
- Experience working closely with Product, Engineering, or Data Science teams
- Experience building or scaling analytical functions
Benefits
- Wellbeing - stay healthy with dedicated support and medical cover
- Work away scheme - gives you the option to work away from your country of residence for up to 90 days in any 12-month period
- Adaptive Working - allows you to work flexibly, around your lifestyle
- Parental leave - to suit everyone embarking on life's great adventure
- Learning Budget - lead your own development with an annual learning budget
- Time off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days ('GC Fridays')