Staff Data Scientist, Risk & AML AI – Scale Fraud Detection

Airwallex; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Airwallex is seeking a Staff Data Scientist for the Risk Product Data Science team in Singapore. You will lead how we proactively identify and mitigate financial crime risk using data across customers, transactions, and networks.

You will scale AI-powered risk detection and collaborate with cross-functional teams to translate complex risks into robust, production-ready solutions. You will drive initiatives in NLP/LLMs, graph analytics and anomaly detection, mentoring others while building

Qualifications

• 7+ years in data science, ML or risk analytics with staff/lead scope.
• Strong ML expertise and production-grade solutions at scale.
• Experience in financial crime detection: NLP/LLMs, entity resolution, graph/network analytics.
• Strong SQL and Python; excellent stakeholder management.

Responsibilities

• Build and scale AI-powered risk detection across name screening, entity resolution, network intelligence and ML.
• Advance AML and financial crime use cases, including transaction monitoring and fraud detection.
• Partner with Risk Product, Engineering, Compliance and Risk Operations to translate complex risk problems into production controls.
• Influence the Risk Product roadmap and raise the technical bar with reusable frameworks and mentoring.

Skills

SQL

Python

Stakeholder management

Communication

Applied ML

Risk analytics

Tools

LLMs

NLP

Graph analytics

Job description

Airwallex is seeking a Staff Data Scientist for the Risk Product Data Science team in Singapore. You will lead how we proactively identify and mitigate financial crime risk using data across customers, transactions, and networks.

You will scale AI-powered risk detection and collaborate with cross-functional teams to translate complex risks into robust, production-ready solutions. You will drive initiatives in NLP/LLMs, graph analytics and anomaly detection, mentoring others while building