Lead Data Scientist - Liquidity at Wise

on-site · full-time · Visa sponsorship

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Responsibilities:
- Lead design, implementation and refinement of forecasting models for liquidity supply and demand across products and regions.
- Integrate forecasts into real-time money movement processes and the treasury operational backoffice for automated decisioning.
- Build bespoke stress-test and scenario analyses for events, product launches and operational incidents.
- Develop product-level liquidity consumption models and tooling to measure usage, drivers and tail risks.
- Present model results, risk assessments and recommendations to senior stakeholders, controllers and Risk (2nd line).
- Collaborate with engineers to productionise models, ensuring scalability, reproducibility and monitoring.

Requirements:
- Strong Python skills and ability to read and validate code; experience shipping models into production.
- Significant hands-on experience with big-data tooling (Hadoop, Spark or equivalents) and cloud data platforms (AWS/GCP/Azure).
- Solid background in statistics, forecasting, machine learning, optimisation or linear algebra applied to financial problems.
- Experience working closely with engineering, product and operations teams and communicating complex concepts clearly.
- Familiarity with liquidity or treasury processes, risk frameworks and stakeholder-facing reporting is desirable.