of the data science lifecycle. Proficiency in Python (or R), SQL, and experience with notebooks, Git workflows, and Power BI. Working knowledge of supervised machine learning (e.g., gradient boosting, logisticregression), evaluation metrics, and experiment design. Exposure to MLOps concepts, cloud platforms (e.g., Azure), and GenAI tools is a strong plus. Structured thinking, strong problem-solving, and clear More ❯
years of experience in general insurance pricing or similar analytical roles. Strong data manipulation abilities with tools such as SAS, R, or Python. Understanding of predictive modelling approaches (e.g., logisticregression, GBMs). What's on Offer Hybrid & Flexible Working: Smart working options plus a minimum of 35 days' annual leave. Health & Well-being: Dental cover, health assessments More ❯
writing, and presenting of research findings Multinational stakeholder management and engagement, including the management of your own steering groups Conduct significant primary quantitative research (hypothesis testing, multiple linear/logisticregression, factor and cluster analysis, Structural Equation Modelling, etc.) Conduct significant primary qualitative research (in depth interviews, focus groups, thematic and content analysis, etc.) Take insights into action More ❯
