Data Scientist – Portfolio Optimisation and Customer Analytics

We are looking for a Data Scientist to join an enterprise analytics and optimisation platform within a global banking environment. The role focuses on portfolio optimisation, pricing, capital allocation, and customer lifetime value analytics across multiple markets and product lines.The platform combines portfolio performance data, customer behaviour signals, and macroeconomic indicators. Analytical outputs are consumed by business, finance, and strategy teams as well as by GenAI-driven reasoning workflows. The environment operates at enterprise scale with structured governance and continuous model industrialisation.

Responsibilities

• Develop portfolio optimisation and customer lifetime value models
• Analyse customer behaviour, profitability drivers, and retention patterns
• Apply statistical modelling, machine learning, and optimisation techniques
• Translate strategic business questions into structured analytical solutions
• Prepare and validate datasets for modelling and scenario analysis
• Collaborate with finance, pricing, and strategy stakeholders
• Expose analytical outputs to downstream systems and LangChain / LangGraph pipelines
• Ensure model robustness, consistency, and governance alignment

Requirements

• Strong hands-on experience in Data Science and advanced analytics Proficiency in Python and common data science libraries (Pandas, NumPy, scikit-learn)
• Proficiency in Python and common scientific libraries (Pandas, NumPy, SciPy, scikit-learn)
• Experience with time series modelling and optimisation techniques
• Strong SQL skills and ability to work with large analytical datasets
• Experience working on analytics platforms such as Databricks or similar
• Ability to translate business objectives into quantitative models
• Experience working in structured enterprise environments
• Fluent English for professional collaboration