5 of 5 Permanent Random Forest Jobs in England

plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling ...

Data Scientist or Operational Research focused role working with large, complex datasets Solid understanding of machine learning techniques such as gradient boosting, random forests and time series modelling Experience building and deploying models used in real world decision making (e.g. ensemble methods, regularised regression) Advanced proficiency in R, including ...

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 and ML Lifecycle technology stacks, such as AWS, Databricks, Google ...

issues in motor or home pricing. Experience with some of the following predictive modelling techniques; GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering, with knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience ...

experience Previous experience within data science Experience in insurance pricing and modelling Experience and detailed technical knowledge of GLMs/Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques Knowledge of statistics and distributions commonly used in insurance Experience in programming languages (e.g. Python, PySpark ...