Высокоуровневая роль Staff-инженера в финтех-единороге. Сочетание продвинутого AI (LLM, графы) и управления рисками в глобальном масштабе.
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Текст:
Hirify AI/Оригинал
TL;DR
Staff Data Scientist (Financial Crime AI): Building AI-powered risk detection and production-grade financial crime controls across customer, transaction, behavioral, network, and external intelligence data with an accent on name screening, entity resolution, graph intelligence, and machine learning. Focus on discovering emerging threats, suspicious communities, coordinated activity, and previously unknown financial crime patterns.
Location: Singapore
Company
Airwallex provides integrated payments, business accounts, spend management, treasury, and embedded finance solutions for global businesses.
What you will do
Lead the data science strategy for AML and financial crime risk controls across Risk Product.
Develop proactive detection capabilities for emerging threats, suspicious behavior, control gaps, and unknown financial crime patterns.
Build and scale AI-powered screening, graph and network intelligence, entity resolution, and machine learning solutions.
Advance name screening, transaction monitoring, and detection of coordinated activity, fraud, and financial crime rings.
Partner with Risk Product, Engineering, Financial Crime Compliance, and Risk Operations to deliver scalable production controls.
Influence the product roadmap, establish reusable frameworks, and mentor Risk Data Science practitioners.
Requirements
7+ years of experience in data science, machine learning, applied AI, risk analytics, or a related quantitative field, with Staff, Lead, or equivalent scope.
Strong expertise in applied machine learning and modern AI, including building and productionizing data-driven solutions at scale.
Experience with NLP or LLMs, entity resolution, information retrieval, graph or network analytics, anomaly detection, or risk scoring.
Strong Python and SQL skills.
Strong communication and stakeholder management skills across Product, Engineering, Risk, Operations, and Compliance.
Nice to have
Experience in fintech, payments, banking, marketplaces, or other regulated or high-risk domains.
Experience with AML, sanctions, PEP screening, adverse media, fraud, trust and safety, or transaction monitoring.
Experience building name screening or adverse media systems.
Familiarity with LLM evaluation, prompt and model experimentation, retrieval quality assessment, and AI observability.
Experience applying graph analytics to detect mule networks, collusive behavior, coordinated account activity, or interconnected high-risk entities.
Culture & Benefits
Work with cross-functional partners across Risk Product, Engineering, Compliance, and Operations.
Operate with high ownership, curiosity, collaboration, and a focus on measurable impact.
Contribute to a global financial platform serving more than 250,000 businesses.
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