13 of 13 Decision Tree Jobs in the UK

theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing). Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks. Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios. Proficiency in More ❯

theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing). Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks. Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios. Proficiency in More ❯

theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing). Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks. Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios. Proficiency in More ❯

Key Skills and Experience: Previous experience within Personal Lines Pricing is advantageous 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 statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics More ❯

studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar. Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.). Solid academic record. Strong computer skills. Knowledge of More ❯

studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar. Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.). Solid academic record. Strong computer skills. Knowledge of More ❯

studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar. Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.). Solid academic record. Strong computer skills. Knowledge of More ❯

studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar. Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.). Solid academic record. Strong computer skills. Knowledge of More ❯

studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar. Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.). Solid academic record. Strong computer skills. Knowledge of More ❯

products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams More ❯

Deep knowledge of product analytics technology, including event streaming and data governance related to GDPR compliance. Proficiency in statistical concepts such as standard deviations, statistical significance, logistic regression, decision trees. . Demonstrated ability to establish industry-standard experimentation and analytics frameworks. At a minimum we require conversational level English language skills. Why? English is our company language and More ❯

techniques across pricing & underwriting Research and leverage new and existing data sources; capturing and explaining trends with innovative data features Clearly communicate results and proposed actions to key decision makers across the business Champion and facilitate automation of reporting, data pipelines and quality assurance Manage, coach and mentor team members, driving a culture of development and excellence across … including knowledge of current trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical and More ❯

techniques across pricing & underwriting Research and leverage new and existing data sources; capturing and explaining trends with innovative data features Clearly communicate results and proposed actions to key decision makers across the business Champion and facilitate automation of reporting, data pipelines and quality assurance Manage, coach and mentor team members, driving a culture of development and excellence across … including knowledge of current trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical and More ❯