6 of 6 Permanent Logistic Regression Jobs in the UK excluding London

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 ...

best practices Key Skills and Experience: Previous experience in tuning and deploying machine learning methods Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps ...

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 ...

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 ...