Position Overview
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.
Key Responsibilities
Strategic Analytics & Product Innovation
- 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
Technical Leadership
- 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
Business Impact
- 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
Required Qualifications
Technical Expertise
- 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
Domain Knowledge
- 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
Business & Leadership Skills
- 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
Preferred Qualifications
- 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
Growth Opportunities
- 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
JR00000443
