Associate Director, FCC Models & Product Risk

About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,200 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us. Attributes We Value We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next. About the Team The Financial Crime Compliance (FCC) team at Airwallex is a strategically vital function operating under a clear Three Lines of Defence model. As the independent second line, FCC owns the global AML/CTF programme, sanctions framework, risk assessment methodology, and governance infrastructure across all global entities. As Airwallex scales into new markets and deepens its engagement with global regulatory bodies, we are building a world-class compliance organization capable of managing complex financial crime risks at scale. This is an environment where you will tackle high-impact challenges, shape global fintech risk strategies, and help establish foundations for long-term growth. What you'll do This role sits within the AML & Sanctions, Governance & Policy pillar of the FCC organization and serves as a critical bridge between regulatory intent and technical execution. In this role, you will serve as the global second-line authority and owner of financial crime detection models, risk analytics, and automated control frameworks. You will own the global methodology, thresholds, and data-scoring models used to identify and mitigate financial crime typologies, be accountable for model governance and liaison with Model Risk Management, and partner with Product Risk and CDO counterparts on technical control deployments as well as the FCC Investigations and FIU team for feedback loops on coverage and tuning optimization. This is a highly quantitative, technically fluent leadership position requiring deep comfort with production logic, automated systems, and data science architectures, balanced with a strong understanding of global AML/Sanctions compliance frameworks and data requirements. This role can be based in the US or EMEA. Responsibilities: Lead the global design and implementation of risk assessment methodologies and quantitative detection models for all financial crime typologies, including money laundering, sanctions circumvention, and behavioral anomalies. Own the quantitative architecture of Airwallex's automated customer risk-rating engines and corporate screening matrices, ensuring behavioral data, risk vectors, and corporate structures are weighted dynamically in real time. Translate complex global compliance obligations into precise, logic-driven product requirements, algorithmic triggers, and risk engineering roadmaps that Product Risk and Engineering teams can build against. Establish and enforce the second-line risk governance framework for new product launches, market expansions, and system changes, ensuring automated compliance controls are fully tested and integrated prior to deployment. Direct the ongoing calibration and statistical tuning of transaction monitoring systems and screening thresholds, utilizing advanced data analytics to minimize false positives while maintaining high detection rates. Govern the deployment of advanced analytics within the compliance ecosystem, including machine learning models and graph databases, while establishing data governance standards to ensure input pipeline integrity. Establish a robust model validation framework to independently test and verify the conceptual soundness, mathematical logic, and regulatory compliance of all financial crime models. Represent Airwallex’s automated model infrastructure before global regulators and Tier-1 banking partners, defending threshold choices, machine learning methodologies, and tuning strategies with statistical evidence. Who you are We're looking for people who meet the minimum requirements for this role. The preferred qualifications are great to have, but are not mandatory. Minimum qualifications: Bachelor’s degree in a highly quantitative or computational discipline such as Data Science, Computer Science, Statistics, Mathematics, Financial Engineering, or Econometrics. Practical fluency in big data environments, query languages (SQL), and algorithmic scripting languages (Python or R). 8 to 12+ years of total experience within financial institutions or technology platforms, with at least 4+ years specifically leading teams focused on FCC model governance, compliance analytics, or transaction monitoring optimization. Deep experience designing, configuring, or tuning enterprise-grade transaction monitoring and sanctions screening engines (proprietary or vendor-based). Proven track record of running data-driven threshold tuning, Above-The-Line/Below-The-Line (ATL/BTL) testing, and statistical segmentations to optimize detection logic. Demonstrated experience defending automated models, tuning choices, and risk-scoring methodologies to global regulators and institutional clearing bank partners. Experience establishing or scaling a model inventory and independent validation framework in line with international regulatory benchmarks. Preferred qualifications: Master’s degree or Ph.D. in Data Science, Artificial Intelligence, Quantitative Finance, or a highly analytical MBA. CAMS-RM (Risk Management), ICA International Diploma in Financial Crime Risk, or technical certifications in Machine Learning or Big Data architectures. Direct experience managing financial crime models in a cloud-native, API-first environment where transaction decisions must be executed algorithmically in milliseconds. Proven track record of moving advanced machine learning, neural networks, or behavioral anomaly detection models out of testing and into live, global compliance operations safely and transparently. Experience utilizing graph databases and link analysis to identify complex, multi-layered financial networks and corporate structures. Experience leading cross-functional squads of data scientists, data engineers, and traditional compliance subject matter experts, acting as a translator between code, mathematics, and regulatory mandates.

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