Senior Data Scientist

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

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