9 of 9 Permanent Logistic Regression Jobs in the UK excluding London

sample design, retrospective analysis, performance analysis, population split analysis and reject analysis.This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

sample design, retrospective analysis, performance analysis, population split analysis and reject analysis.This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

Python skills with a strong foundation in software and data engineering best practices. Deep knowledge of statistical and machine learning models—gradient boosted trees, logistic regression, neural networks, survival analysis, etc. Comprehensive understanding of statistics: hypothesis testing, confidence intervals, bootstrap. Experience with end-to-end model development ...

skills with good understanding of best practices in software engineering and data engineeringIn-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etcSolid knowledge of statistics: hypothesis testing, confidence intervals, bootstrapExperience of end-to-end model development and maintenance ...

Toolkit Using gradient boosting (e.g. XGBoost, LightGBM, CatBoost) as the default for tabular prediction. Recognising when simpler, more interpretable models, such as regularised logistic regression or well‐constrained decision trees, are the better choice. Applying clustering and segmentation techniques (e.g. k‐means, hierarchical or sequence‐based clustering ...

reporting, early warning systems, customer segmentation and scoring, credit risk insights, or personalisation. • Strong understanding of AI and data science techniques, including statistical modelling, logistic regression, NLP, LLMs, Generative AI, and Agentic AI. • Strong track record of applying Agile product development methodologies. • Customer-centric mindset with a proven ...

consultants on analytic client engagements involving descriptive, predictive, and prescriptive analysis through the consumer lending portfolio lifecycle, leveraging a variety of techniques (e.g., segmentation, logistic regression, etc). You will deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers. You will design ...

areas: data science; epidemiology; administrative dataset analysis; maternal health; statistical analysis of routinely collected health care or clinical trial datasets using techniques such as logistic regression, imputation of missing data, multilevel modelling. . Application Interview Presentation Strong knowledge of research methods and techniques appropriate to the discipline ...

Advanced coding skills in a range of analytical software packages (eg R, SQL). Advanced statistical and/or mathematical skills including e.g. linear, logistic, cox regression, analysis of variance, repeated measures, survival analyses Advanced IT skills including Microsoft office. Excellent written and presentation communication skills. Effective stakeholder ...