Senior Data Scientist

Responsibilities:

• Develop machine learning and statistical models for fraud prevention, risk scoring, and credit underwriting.
• Analyse large-scale behavioural and transactional datasets to identify patterns, anomalies, and emerging fraud trends.
• Design and run experiments to evaluate, compare, and improve model performance.
• Partner with engineering to deploy models into production and ensure they are reliable, observable, and performant at scale.
• Monitor live models for drift and degradation, and lead retraining and improvement cycles.
• Collaborate with product and risk teams to translate business problems into modelling solutions.

Requirements:

• Bachelor's degree or higher in Computer Science, Statistics, Applied Mathematics, or a related field.
• 5+ years of experience in data science, with exposure to fintech or financial services preferred.
• Strong expertise in Python and SQL, and hands-on experience with ML frameworks such as scikit- learn, XGBoost, PyTorch, or TensorFlow.
• Solid foundation in classical machine learning, statistical modelling, and experiment design.
• Experience taking models from notebook to production, including monitoring and iteration.
• Ability to communicate complex findings clearly to technical and non-technical stakeholders.