7 of 7 Permanent Logistic Regression Jobs

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 ❯

e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 4+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression PREFERRED QUALIFICATIONS - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience - Experience managing data pipelines Amazon is an equal opportunity employer and does 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 ❯

based on key findings from analysis · Create dashboards to answer key client questions within Power BI · With the assistance of senior analysts creating predictive models utilising methods such as Logistic Regression, CHAID and Clustering techniques · Answering quick questions using data to help guide business decisions · Developing and maintaining strong relationships with stakeholders · Peer review of colleague's work … analysing large volumes of data and a solid understanding of database principles and efficiencies desirable. Ideally in SQL server or Databricks. · Basic statistics: familiarity with averages, deviations, correlation and regression is required · A quality first approach to work, with a strong attention to detail. · Excellent written communication: creating clear, concise and actionable materials for the client. · Confident oral communication 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 ❯

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 ❯