Senior Data Scientist

Position OverviewWe 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.Key ResponsibilitiesStrategic Analytics & Product InnovationDesign and implement advanced machine learning models for credit risk assessment, fraud detection, customer lifetime value prediction, and personalized product recommendationsPartner with product teams to translate business challenges into data science solutions that drive measurable impactBuild predictive models for customer churn, acquisition optimisation, and engagement strategiesDevelop scoring systems for loan decisioning and transaction monitoringTechnical LeadershipLead end-to-end model development lifecycle from experimentation to production deploymentPartner with engineering teams to design and deploy scalable ML pipelines using modern cloud infrastructureEstablish best practices for model governance, monitoring, and validationMentor junior data scientists and promote a culture of analytical excellenceBusiness ImpactCollaborate with stakeholders across Risk, Marketing, Product, and Engineering to identify opportunities for data-driven optimisationCommunicate complex technical concepts and insights to non-technical executives through compelling data storytellingDesign and analyze A/B tests to measure feature impact and guide product decisionsRequired QualificationsTechnical Expertise5+ years of experience in data science, with at least 2 years in fintech, banking, or financial servicesExpert-level proficiency in Python and ML frameworks (Tensorflow, PyTorch, XGBoost)Strong foundation in statistical methods, hypothesis testing, and experimental designProduction experience with SQL and working with large-scale datasets (terabytes+)Proven track record deploying and maintaining ML model pipelines in production environmentsDomain KnowledgeDeep understanding of financial services concepts including credit risk, fraud patterns, regulatory compliance (KYC / AML), and customer behaviourExperience with time-series forecasting, anomaly detection, and classification problemsFamiliarity with ML model explainability techniques (SHAP, LIME) and responsible AI practicesKnowledge of model governance frameworksBusiness & Leadership SkillsOutstanding problem-solving abilities with a product-minded approachExcellent communication skills with ability to influence key stakeholdersCollaborative team player who thrives in fast-paced, agile environmentsStrong business acumen and ability to balance technical rigour with practical constraintsPreferred QualificationsExperience with real-time ML systems and stream processing (Kafka, Spark Streaming)Knowledge of LLMs and generative AI applications in bankingExperience with MLOps tools (MLflow, Kubeflow, SageMaker)Prior experience building recommendation engines or personalisation systemsGrowth OpportunitiesShape the analytics culture and best practices across the organizationOpportunity to influence product strategy through data-driven insightsCareer progression toward senior leadership roles in data and analytics