Threat and Analytics Lead

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.

Responsibilities

Builds GoCardless's data-driven understanding of fraud and financial crime risk; Brings specialist analytical expertise to fraud and financial crime domains; Helps the business understand emerging threats, measure how well existing controls are working, and identify where prevention and detection need to get stronger; Informs strategy and investment prioritisation with evidence and insights; Works closely with Product, Engineering, Operations and Data Science to analyse large, complex datasets and surface patterns, trends and risk concentrations across the customer lifecycle; Works with teams who own fraud and financial crime strategy, governance, policy and operational delivery

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; Takes ownership of problems, brings structure to ambiguity, and drives 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 - work away from country of residence for up to 90 days in any 12 month period; Adaptive Working - work flexibly around your lifestyle; Parental leave - to suit everyone embarking on life's great adventure; Learning Budget - annual learning budget; Time off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days ('GC Fridays')