What you'll be doing

Work closely with Treasury operations to develop supply and demand forecasts and incorporate them into real-time money movement processes across a multi-region portfolio of products and currencies.
Conduct rigorous data analysis to support liquidity efficiency initiatives, ensuring a balance between sufficiency and excess.
Collaborate with engineering teams to implement models within the treasury's operational backoffice, ensuring scalability and operational efficiency.
Develop bespoke models and analyses in preparation for stress events and new product launches.
Develop models and infrastructure for understanding liquidity consumption by company’s products.
Partner with product and operational teams to translate complex liquidity risk scenarios into actionable insights for customer-focused solutions.
Document and present model results and risk assessments to senior stakeholders, controllers, and the Risk team, explaining complex concepts and proposing strategies that align with the company’s risk appetite and business objectives.

Requirements

Strong Python knowledge with the ability to read through code and experience collaborating with engineers.
Experience with big data technologies such as Hadoop, Spark, or similar; familiarity with cloud platforms (AWS, GCP, Azure) and data warehousing solutions.
Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation.
A strong product mindset with the ability to operate autonomously while working in a cross-functional and cross-team environment.
Good communication skills with the ability to convey information to non-technical individuals.
Strong problem-solving skills with the ability to refine problem statements and devise effective solutions.

Experience in supply/demand modelling and forecasting, potentially in supply chain optimisation or liquidity management within a financial company.