Senior Data Scientist

We are seeking an exceptional Senior Data Scientist to drive product innovation through advanced analytics, experimentation, and machine learning. Embedded within cross-functional product teams, you will deliver measurable business impact by building and deploying solutions across fraud detection, credit decisioning, and user experience optimisation. You will own the full lifecycle – from designing experiments and developing models to production deployment and performance monitoring. This role demands both technical excellence and strategic thinking to identify high-impact opportunities and deliver data-driven results in a fast-paced fintech environment.

• Design and implement advanced machine learning models for credit risk assessment, fraud detection, customer lifetime value prediction, and personalized product recommendations
• Partner with product teams to translate business challenges into data science solutions that drive measurable impact
• Build predictive models for customer churn, acquisition optimisation, and engagement strategies
• Develop scoring systems for loan decisioning and transaction monitoring

• Lead end-to-end model development lifecycle from experimentation to production deployment
• Partner with engineering teams to design and deploy scalable ML pipelines using modern cloud infrastructure
• Establish best practices for model governance, monitoring, and validation
• Mentor junior data scientists and promote a culture of analytical excellence

• Collaborate with stakeholders across Risk, Marketing, Product, and Engineering to identify opportunities for data-driven optimisation
• Communicate complex technical concepts and insights to non-technical executives through compelling data storytelling
• Design and analyze A/B tests to measure feature impact and guide product decisions

• 5+ years of experience in data science, with at least 2 years in fintech, banking, or financial services
• Expert-level proficiency in Python and ML frameworks (Tensorflow, PyTorch, XGBoost)

• Strong foundation in statistical methods, hypothesis testing, and experimental design
• Production experience with SQL and working with large-scale datasets (terabytes+)
• Proven track record deploying and maintaining ML model pipelines in production environments

• Deep understanding of financial services concepts including credit risk, fraud patterns, regulatory compliance (KYC / AML), and customer behaviour
• Experience with time-series forecasting, anomaly detection, and classification problems
• Familiarity with ML model explainability techniques (SHAP, LIME) and responsible AI practices
• Knowledge of model governance frameworks

• Outstanding problem-solving abilities with a product-minded approach
• Excellent communication skills with ability to influence key stakeholders
• Collaborative team player who thrives in fast-paced, agile environments
• Strong business acumen and ability to balance technical rigour with practical constraints

• Experience with real-time ML systems and stream processing (Kafka, Spark Streaming)
• Knowledge of LLMs and generative AI applications in banking
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker)
• Prior experience building recommendation engines or personalisation systems

• Shape the analytics culture and best practices across the organization
• Opportunity to influence product strategy through data-driven insights
• Career progression toward senior leadership roles in data and analytics