Senior AML Systems and Data Analyst - BOQ Group

About the role At BOQ Group, we're continuing to strengthen and evolve our Financial Crime capability, and we're looking for a Senior AML Systems and Data Analyst to play a key role in shaping how we detect, monitor and respond to financial crime risks across the Group. This role sits within our Financial Crime Operations team and combines financial crime expertise, data analytics and stakeholder engagement to ensure our detection controls remain effective, risk-based and aligned to regulatory expectations. Working across transaction monitoring, customer risk assessment, screening and other financial crime controls, you'll help design, optimise and continuously enhance the systems, models and rules that protect our customers and business from financial crime threats. You'll analyse emerging financial crime typologies, identify detection gaps and partner with stakeholders across Operations, Compliance, Risk, Technology and Data to improve the effectiveness of our monitoring and screening capabilities. The role also offers the opportunity to contribute to transformation initiatives focused on analytics, automation, artificial intelligence and machine learning, helping the team continue to evolve its approach to financial crime detection. Day to day, you'll be involved in reviewing and tuning detection scenarios, conducting coverage and effectiveness assessments, supporting system and data enhancements, delivering analytical insights and reporting, and helping ensure our financial crime controls remain fit for purpose in a changing regulatory environment. You'll also play an important role in supporting change initiatives, governance activities, audits and regulatory reviews while driving continuous improvement across the function.

About you You – our successful candidate is someone who will bring experience in Financial Crime, AML, Fraud, Risk Analytics or Data Analytics within a banking or financial services environment, along with a genuine passion for using data to solve complex problems and improve risk outcomes. You understand how AML/CTF controls operate in practice and have experience working with transaction monitoring, customer risk assessment, screening or related financial crime systems. You'll likely have experience designing, tuning or optimising financial crime detection rules, scenarios or models and be comfortable working with large datasets and analytics tools. Strong SQL skills are important, while experience with Python, Power BI, SAS Enterprise Guide, VBA or similar technologies will be highly regarded. Exposure to financial crime platforms such as NetReveal, Safer Payments, SAS or comparable monitoring and screening solutions would also be beneficial.