7 of 7 Permanent Logistic Regression Jobs

quantitative subject (e.g. computer science, mathematics, engineering, science, economics or finance). A good understanding of statistical modelling knowledge or any machine learning technique knowledge (such as hypothesis testing, regression, logistic regression, random forest, etc.) Good stakeholder management experience. Comfortable presenting to senior leadership and C-suite. Experience in conducting A/B testing experimentation Strong experience More ❯

and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). More ❯

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, logistic regression), 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 ❯

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, logistic regression), 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 logistic regression, 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 ❯

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/logistic regression, 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 ❯

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., logistic regression, 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 ❯