Job Description

Job Purpose To design, develop and optimise machine learning, AI and decisioning solutions that drive customer, risk and operational outcomes across Personal and Private Banking (PPB) and Digital channels. Purpose Apply advanced analytics, machine learning and AI techniques to solve business problems, improve customer experiences and support intelligent decisioning. The role focuses on feature engineering, model development, experimentation and decision science while leveraging the Databricks platform to deliver scalable and reusable analytical assets. Requirements What You’ll Do Build and optimise ML models using Databricks, MLflow, Python & SQL Develop customer, propensity, retention, risk, fraud and decisioning models Build reusable features using Databricks Feature Store Apply Generative AI & LLMs to innovative business use cases Turn complex data into actionable insights and measurable business value Partner with business, product, risk and technology teams Mentor and inspire junior Data Scientists What You Bring Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, Actuarial Science, Econometrics or a related field Strong hands-on Databricks + Python + SQL + Machine Learning experience Experience taking data science solutions from concept to production Strong statistical modelling, feature engineering and model validation skills Commercial mindset with excellent stakeholder and communication skills Master’s/PhD and relevant Databricks, Azure, AWS, GCP or SAS certifications are a plus. ​ Your Tech Toolkit You'll ideally bring strong hands-on experience with: Databricks — Notebooks, Workflows, MLflow and distributed compute Databricks Feature Engineering & Feature Store Python & SQL Machine Learning & Statistical Modelling Predictive & Prescriptive Analytics Decision Science & Optimisation Feature Engineering & Feature Selection Experimentation & Model Validation Generative AI, LLMs & Prompt Engineering Data Visualisation & Storytelling