Staff Data Scientist, Algorithm (Risk Product – AML & Financial Crime)

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

 How you'll make impact

As a Staff Data Scientist in the Risk Product Data Science team, you’ll lead how Airwallex proactively identifies and mitigates financial crime risk. You’ll work across customer, transaction, behavioural, network and external intelligence data to detect known and emerging risks, uncover suspicious communities and coordinated activity, and improve how we screen customers and counterparties for financial crime exposure.

• Build and scale AI-powered risk detection capabilities across name screening, entity resolution, network intelligence and machine learning.

• Advance AML and financial crime use cases, including transaction monitoring, detection of coordinated activity, and identification of fraud or financial crime rings.

• Partner with Risk Product, Engineering, Financial Crime Compliance and Risk Operations to translate complex risk problems into effective, scalable production controls.

• Influence the Risk Product roadmap and raise the technical bar for Risk Data Science through technical leadership, reusable frameworks and mentoring.

You’ll work from our Singapore office five days a week.

What we're looking for

Essentials

• 7+ years of experience in Data Science, Machine Learning, Applied AI, Risk Analytics or a related quantitative field, with demonstrated impact at Staff, Lead or equivalent scope.

• Strong expertise in applied machine learning and modern AI, with experience building and productionising data-driven solutions at scale.

• Experience in one or more areas relevant to financial crime detection, such as NLP and LLMs, entity resolution, information retrieval, graph or network analytics, anomaly detection or risk scoring.

• Strong SQL and Python skills.

• Strong communication and stakeholder management skills, with the ability to influence senior partners across Product, Engineering, Risk, Operations and Compliance.

Preferred

• Experience in fintech, payments, banking, marketplaces or another regulated or high-risk domain.

• Experience in AML, financial crime, sanctions, PEP screening, adverse media, fraud, trust and safety or transaction monitoring.

• Experience building or improving name-screening or adverse-media systems.

• Familiarity with modern LLM evaluation, prompt and model experimentation, retrieval-quality assessment and AI observability.

• Experience applying graph analytics to detect mule networks, collusive behaviour, coordinated account activity or interconnected high-risk entities.

• Experience developing proactive risk-discovery capabilities rather than exclusively optimising existing supervised models or rules.

You'll thrive here if

• You're comfortable owning the roadmap yourself.

• You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.

• You connect dots across functions and hold the big picture without losing grip on the details.

• You simplify complexity rather than hiding behind it.

• You over-communicate by design. You'd rather flag something early than let it become a surprise.

Learn more about your team

Risk Platform builds the decisioning infrastructure that sits between Airwallex and every dollar that moves through it, protecting 150,000+ businesses moving over US$260 billion a year across 150+ countries and 60+ currencies, and deciding, often in milliseconds, whether a new signup is real, a payment is safe, or a login is who they claim to be. The hard part is that fraud evolves fast, and every decision carries a two-sided cost: miss an attack and money is lost, over-block and a legitimate business can't get paid. We build this with streaming pipelines processing billions of events a day, graph databases exposing coordinated fraud rings, ML models scoring every transaction, and LLM agents that triage alerts. You don't need a fintech background, just an appetite for adversarial systems problems where the scoreboard is measured in dollars. If you want to help scale one of the world's fastest-growing financial platforms safely, this is the team.

Applicant Safety Policy: Fraud and Third-Party Recruiters

To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.