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Airwallex

Runs global payments and accounts for businesses

Staff Data Scientist - Algorithm, Financial Markets

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • At least 7 years of industry experience and an advanced degree, such as a PhD or MS, in a quantitative field such as Statistics, Engineering, Sciences, Computer Science, or Economics.
  • Significant experience applying statistics, machine learning, or optimisation to financial markets, trading, fintech, or other dynamic decision systems.
  • Strong understanding of FX, execution, pricing, liquidity, market risk, or related quantitative domains.
  • Expert Python skills and strong SQL skills.
  • Strong foundations in time-series modelling, statistical inference, optimisation, and experimental design.
  • Ability to do schema design and dimensional data modelling, taking models from research or prototyping into reliable production systems.
  • Proven ability to set direction, influence and communicate with senior stakeholders, and deliver through cross-functional teams.

Responsibilities

  • Own and drive the technical direction and modelling roadmap for the FX product, identifying high-impact opportunities and prioritising work in collaboration with Product Managers.
  • Develop and productionise models to forecast and monitor FX rate volatility, providing actionable insights to support trading and execution strategy.
  • Apply statistical and machine learning models to optimise FX trade execution, focusing on minimising cost, improving routing efficiency, and managing market risk exposure.
  • Establish robust backtesting, validation, monitoring, and governance practices for financial-market models.
  • Partner with Product Managers, Traders, Risk, Engineering, and other stakeholders to translate analytical findings into trading and product decisions.
  • Define success metrics and evaluate the incremental impact of models and strategies in production.
  • Move quickly from analysis to decision-ready recommendations, communicating clearly with executives and cross-functional partners, including when data or problems are ambiguous.
  • Conduct customer and commercial analysis where it directly informs FX strategy, pricing, or product priorities.
  • Build systems of decision that help teams understand what changed, determine what to do next, and learn whether the action worked, owning the AI analytics harness around the analysis, including semantic layers, context retrieval, evaluation infrastructure, validation gates, and governance.
  • Build systems of action that use machine learning and AI to shape product behavior, ranking, pricing, risk, allocation, and customer experiences, including designing how intelligent systems reason, use tools, operate within guardrails, execute workflows, and measure incremental impact.
  • Structure ambiguous problems, design experiments, identify confounding factors, challenge misleading conclusions, and build production systems that produce reliable outcomes repeatedly.

Desired Qualifications

  • Experience in technology, financial services, a trading environment, and/or a high-growth environment.
  • Experience with R or other quantitative tools.

About the Company

Airwallex

Runs global payments and accounts for businesses

Airwallex runs a financial platform for businesses that sell, buy and operate across borders, from startups to large enterprises. Its multi-currency accounts let customers receive and hold money locally, then pay overseas suppliers without converting every sale into their home currency. Businesses also use its corporate cards and expense controls to manage spending, while online sellers accept customer payments through its checkout tools. Finance teams work in a web app, and developers embed the services in other software; Airwallex earns transaction fees and charges for paid software plans. Founded in Melbourne in 2015, Airwallex has dual headquarters in Singapore and San Francisco.

Company size
1,001-5,000
Company stage
Series H
Total funding
$1.7B
Headquarters
Singapore, Singapore
Founded
2015

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