1 to 25 of 37 Decision Tree Jobs in England

Azure-native tools: ARM/Bicep, Terraform, Azure DevOps or GitHub Actions, and monitoring solutions. Excellent written communication skills; able to produce diagrams, decision trees, and design docs that teams can rely on. A mindset oriented towards collaboration, mentorship, and cross-functional influence. If you are interested ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...

significant impact on our customer retention and long-term success. Key Responsibilities: Design, train, validate, and optimize classical ML models (e.g., regression, decision trees, random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn … tasks toward high-level goals with limited human oversight. Integrate classical machine learning models into agentic AI workflows where predictive capabilities inform planning, decision-making, and action selection. Develop and evaluate interfaces between agentic components and external tools, APIs, or systems to enable real-world actions. Work closely ...