Lead Data Scientist - Treasury Liquidity

In this role, you design and refine models to forecast liquidity needs and manage liquidity risk across regions. You will partner with Treasury, product, and engineering teams to translate insights into scalable, data-driven solutions. Your work supports timely cash movements and resilient operations, including stress scenarios and new product launches. This is a hands-on opportunity to shape liquidity strategy and risk governance in a fast-moving fintech environment.

• Develop supply/demand forecasts and integrate them into real-time money movement across multi-region product/currency portfolios
• Perform rigorous data analysis to improve liquidity efficiency while balancing sufficiency and excess
• Collaborate with engineering to implement models within treasury backoffice for scalability and efficiency
• Create bespoke models and analyses for stress events and new product launches
• Build models to quantify liquidity consumption by products and translate risk scenarios into actionable insights
• Document and present model results and risk assessments to senior stakeholders, controllers, and Risk team
• Explain complex concepts to non-technical audiences and align strategies with risk appetite and business objectives

• Strong Python knowledge and ability to read code
• Experience collaborating with engineers
• Experience with big data technologies (Hadoop, Spark or similar)
• Familiarity with cloud platforms (AWS, GCP, Azure) and data warehousing
• Knowledge in statistics, machine learning, linear algebra, optimisation
• Strong product mindset and ability to work autonomously in cross-functional teams
• Good communication skills to convey technical concepts to non-technical stakeholders
• Strong problem-solving skills to refine problems and find solutions

• Cross-functional collaboration
• Clear communication
• Autonomy and initiative
• Python
• Hadoop
• Spark