Data Scientist London Insurance Market City, London (3-4 days per week onsite) Permanent Circa £75,000 per annum benefits 15% bonus A fantastic opportunity has arisen for a Data Scientist, ideally with previous Insurance experience, to join a well respected London Market Insurer and play an important position in delivering requirements for the Digital Trading Division, focussing on the delivery of Digital Follow data science use cases. Under the guidance of the Data Science Manager, you will assist in defining the strategic data requirements for delivery of data consumption use cases. You need to be comfortable interacting with all teams within the business to understand, capture, prioritise and document business and technical requirements leading to the deployment of automated, optimised and highly effective analytics solutions. You will have exceptional data science and programming skills with additional statistical, data manipulation and data analysis capability. This all-round knowledge will be key to ensure effective communication and collaboration with the data analytics and actuarial teams. Key responsibilities: Helps the Data Science Manager to deliver: a) Digital Data cleansing (e.g. matching of premium and claims for digital business), mining and analysing internal databases and external Broker data. b) Work alongside actuarial team to project data and analyse risk and class performance. c) Using data science/AI techniques to automate and build out rule sets to grow and maximise profitability for Digital Follow opportunities. d) Optimise portfolios through the regular data monitoring and analysis of external (and internal) data. Skills, Knowledge and Experience: • Expert in data science techniques • Advanced programming skills (Python an advantage) • Strong statistical, data manipulation and data analysis skills • Strong academic background • Demonstrable' actuarial and/or data experience preferably in a Lloyd's environment • Good written and face to face communication skills with people across the business (technical and non-technical) • Experience in a similar role supporting the development of data consumption use cases an advantage • Experience working with Azure data technology stack such as Data Factory, SQL, Synapse Analytics, PowerBI an advantage