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 ❯
questions and developing hypotheses, and can collaborate with non-Data Scientists to clarify assumptions and influence decisions. You have extensive experience using various analysis techniques, such as linear and logisticregression, significance testing, and statistical modeling. You have a keen interest in using AI tools to support data exploration and analysis, and already have some experience in doing 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 ❯
