22 of 22 Decision Tree Jobs in England

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI More ❯

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI More ❯

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI 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 ❯

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 ❯

. Microsoft suite - Excel, Powerpoint etc. Languages: Python, SQL, Git. Working towards more complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), Principal Component Analysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and build convincing stories. 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 ❯

to solve complex business problems. Proficiency in Python and libraries such as Scikit-learn, TensorFlow, Keras, and PyTorch. Solid foundation in statistics, probability, and core ML algorithms (regression, decision trees, gradient descent, SVMs, etc.). Hands-on experience with transformer architectures and LLMs. Familiarity with LangChain, LlamaIndex, or similar frameworks for building LLM-based applications. Ability to convert 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 ❯

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 ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯

with consistency, accuracy, and accountability - all at speed and scale. About the job As a Senior Data Scientist, you will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business … control. Strong SQL skills and familiarity with databases like Redshift, Postgres, or Microsoft SQL Server. Solid understanding of machine learning algorithms, concepts, and applications, including regression, K-means, decision trees, neural networks, as well as exposure to generative AI and large language models (LLMs). Hands-on experience with cloud platforms such as AWS or Azure. We're … accuracy, and accountability - all at speed and scale. Job Details About the job As a Senior Data Scientist, you will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business 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 ❯

of data science & statistical techniques across pricing & underwriting Research and leverage new and existing data sources; capturing and explaining trends with innovative data features Communicate results to key decision makers across the business for action based on the results of pricing analysis Review observed & expected performance of key accounts Collaborate with peers in pricing, underwriting and data science … team members Key Skills and Experience: Previous experience within general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics More ❯

of data science & statistical techniques across pricing & underwriting Research and leverage new and existing data sources; capturing and explaining trends with innovative data features Communicate results to key decision makers across the business for action based on the results of pricing analysis Review observed & expected performance of key accounts Collaborate with peers in pricing, underwriting and data science … team members Key Skills and Experience: Previous experience within general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics More ❯