Lead Data Scientist

Salary

Core Qualifications

Key Responsibilities

• •Lead, mentor and motivate a data science team (up to10 people) and set the technical direction and standards
• •Collaborate within a cross-functional digital team, including Product Management, Engineering and Design
• •Bridge the gap between business problems and data science solutions, turning opportunities into impactful, production-ready models
• •Utilise strong analytical and modelling skills to design, build, and validate machine learning solutions, particularly tree-based methods (e.g. XGBoost, GBM, LightGBM), neural networks, and transformer-based approaches
• •Define and lead the end-to-end lifecycle of data products in an agile environment, from problem framing and experimentation through to deployment and monitoring
• •Conduct and document detailed analysis, including business case development, to prioritise use cases and clearly communicate trade-offs and expected value to stakeholders
• •Work closely with data and platform engineers on ETL pipelines, containerised solutions (e.g. Docker, Kubernetes), and cloud-based environments (e.g. GCP, AWS, Azure), with exposure to modern data platforms such as Snowflake and Databricks
• •Collaborate with cross-functional Agile teams (Engineering, Product, Design, QA) in remote and on-site settings, applying appropriate governance and engagement models to data projects
• •Provide BAU support for existing models and data products, while actively managing demand, prioritisation, and stakeholder expectations to create space for strategic, high-impact data science initiatives