Senior Data Scientist – Applied Machine Learning

• Translate customer and business problems into clear analytical and machine-learning objectives. • Work with large datasets, event data and feature stores to identify useful signals and build predictive features. • Develop, evaluate and improve models for use cases such as propensity, personalisation, growth and retention. • Apply appropriate techniques across classification, regression, experimentation, forecasting and other applied data-science problems. • Take models through the full product lifecycle, including deployment, automation, monitoring, retraining and ongoing maintenance. • Help improve data quality, feature pipelines, model monitoring, drift detection and ML Ops practices. • Work with product managers and business stakeholders to define success measures and translate model outputs into action. • Explain technical approaches, assumptions and results clearly to technical and non-technical audiences. • Collaborate with data, software and AI engineering teams to review solutions, improve coding standards and share knowledge. • Contribute to technical documentation, design discussions and delivery planning. • Work with external partners or vendors where required to deliver the right solution.