Company descriptionLocation: London (hybrid working 3 office days per week) Employment Type: Permanent, full time Think the AA is just about roadside assistance? Think again. For over a century, we've been evolving and adapting. Today, as the nation's leading motoring organisation, we offer a wide range of products and services to millions of customers. From roadside assistance to home and motor insurance, and the latest driving technologies, we have it all. As we continue to expand, diversify, and modernise, joining us as a Data Scientist, means you'll play a crucial role in our success and be part of this exciting motoring journey. Our Chief Operating Office (COO) are the backbone of The AA, providing both stability and structure to support growth and innovation. We are the drivers of change. #LI-HybridThis is the jobAs a Data Scientist, you’ll apply advanced analytics and data science techniques to solve complex business problems, deliver actionable insights, and support strategic decision-making. You’ll work closely with stakeholders across the business to ensure data is leveraged effectively and responsibly.What will I be doing?As a Data Scientist, you’ll implement visionary ideas to deliver data science products. In doing so, you will:Develop and deploy machine learning and statistical models using connected car, behavioural and operational dataDesign data science solutions that improve mobility services, propositions and customer outcomesBuild and test hypotheses through rapid prototyping using Python, Spark and DatabricksTranslate complex analytical outputs into clear, actionable insights for technical and non-technical stakeholdersDelivery ongoing optimisation and continuous improvement to existing model suiteWork closely with engineering to embed models into live products and platformsShape and influence the data science and analytics agenda across Product, Operations and MarketingIdentify new data sources and analytical techniques to increase the value of connected car dataPromote best practices in data science, model development, feature engineering and MLOps including robust documentationEnsure insights drive real business action and inform future strategyWhat do I need?Customer Analytics experience developing predictive modelsExperience developing predictive and machine learning models in PythonStrong grounding in statistical modelling (e.g. regression, GLMs, decision trees, neural networks, Bayesian methods)Experience working with large, complex datasets, ideally including connected car, IoT, telematics or time-series dataAbility to deliver analysis in an agile, production-focused environmentAdditional information