What we’re looking for

We are looking for a highly capable and curious Data Scientist to help build the data and ML capabilities powering our B2B payments platform, which processes over US$2B annually across multiple currencies. You’ll work closely with engineering and product teams to solve complex problems, drive data-driven decisions, and own models end-to-end — from exploration to deployment. If you're excited by impactful work in a fast-moving fintech environment, we’d love to meet you.

Responsibilities

• Lead and mentor a cross-functional data team (data science, data engineering, analytics) to ensure high-quality, timely execution.
• Own end-to-end delivery of machine learning models — from scoping and development to deployment, monitoring, and iteration.
• Analyse large, complex datasets to identify insights, diagnose issues, and validate opportunities that drive measurable business impact.
• Oversee development of reliable data pipelines, models, and dashboards to support operational, product, and compliance needs.
• Design and run A/B tests; define and monitor key metrics; forecast trends and communicate insights to leadership.
• Collaborate closely with Product, Engineering, Operations, and Compliance to translate business problems into actionable data and ML solutions — Fraud & Anomaly Detection, Dynamic Routing.
• Identify and prioritise high-value opportunities where ML, analytics, or improved data infrastructure can enhance platform performance and growth.

Qualifications

• 5+ years of hands-on experience in data science or machine learning.
• Strong proficiency in Python and SQL, plus ML libraries (scikit-learn, PyTorch/TensorFlow).
• Proven track record of deploying ML models into production environments.
• Experience building reliable pipelines, working with real-time / batch data, and monitoring model performance.
• Strong communication skills and the ability to work across technical and non-technical teams.
• Experience working in fintech, payments, or high-growth tech environments (preferred).
• Familiarity with APIs, microservices, and MLOps tooling (Airflow, CI/CD, monitoring).