Staff Data Scientist, FX Algorithms

About the role

Airwallex is hiring a Staff Data Scientist for its FX algorithm team in Singapore. The Financial Markets team builds the data science capabilities that support FX pricing, execution and risk decisions. You will own the modelling and analysis roadmap for the FX product and turn statistical and machine learning work into better trading, product and commercial decisions. The role is based in the Singapore office five days a week.

Key responsibilities

• Own and drive the technical direction and modelling roadmap for the FX product, prioritising work with Product Managers.
• Develop and productionise models to forecast and monitor FX rate volatility, supporting trading and execution strategy.
• Apply statistical and machine learning models to optimise FX trade execution, minimising cost, improving routing efficiency and managing market risk exposure.
• Establish backtesting, validation, monitoring and governance practices for financial-market models.
• Partner with Product Managers, Traders, Risk, Engineering and others to turn 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, even when the data or problem is ambiguous.
• Conduct customer and commercial analysis where it informs FX strategy, pricing or product priorities.

Required profile

• 7+ years of industry experience and an advanced degree (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.
• Preferred: experience in technology, financial services, a trading environment and/or a high-growth environment.

Required skills

• Expert Python and strong SQL; R or other quantitative tools is a plus.
• Foundations in time-series modelling, statistical inference, optimisation and experimental design.
• Schema design and dimensional data modelling, taking models from research into production.
• Ability to set direction, influence and communicate with senior stakeholders and deliver through cross-functional teams.