1 to 11 of 11 Permanent Decision Tree Jobs in the UK

to End Learning Designer to join their Open Research team and working collaboratively with the teams Content Owner to develop a 'Decision Tree' style piece of eLearning content. The position will be a day rate contract for 20 - 25 days worth of work in July, though there … Person The ideal candidate will have experience with: Designing and developing digital learning programmes Articulate Storyline and/or Rise Creating 'Decision Tree' style eLearning content (desirable) Designing and developing content for professionals Aside from a competitive daily rate, this contract offers the opportunity to work with more »

scikit-learn etc.) or highly transferable skill analogues Experience developing and evaluating models using at least one of the following technologies: —- Gradient-boosted decision trees (e.g. Catboost, XGBoost) —- Reinforcement learning —- Recommendation systems —- Large language models Able to train, tune and evaluate models and prepare them for production deployment more »

Risk Models, Impairment, Capital, Basel, AIRB, Scorecards, Decision Science, Stress Testing, SAL, SQL, PD, LGD, EAD, IFRS9, Logistic Regression, Decision Tree, Probability of Default, Exposure of Default, Loss Given Default more »

language e.g. SAS Experience in some of the following predictive modelling techniques e.g. Logistic regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets. Experience of Emblem and Radar. Experience in the use of programming language such as Matlab more »

ethical use of AI, ensuring compliance with internal policies and external regulations. Deep understanding of traditional AI techniques: regression, classification, forecasting, clustering (e.g., Decision Trees, XGBoost, ARIMA, etc.) Strong understanding of programmatic LLM risk controls: output format validation, output context validation, content moderation etc. There is a lot more »

key areas. Key Responsibilities: Batch Workload Integration: File Transfer Artefacts Data Consumption: Business Intelligence - Advisory Report Business Analytics - Alteryx Data Science - Decision Tree Foundational Data Management: Data Quality Management - Tool Evaluation Master & Reference Data Management - Advisory Report Meta Data Management - Artefacts Data Optimization: Query Optimization (Data Warehouse … quality management, metadata management, and master data management. Proficient in query optimization and data warehouse management. Experience with modern data science techniques, including decision trees and machine learning operations (ML Ops). Ability to evaluate and recommend tools for data quality management. Familiarity with real-time data integration more »

key areas. Key Responsibilities: Batch Workload Integration: File Transfer Artefacts Data Consumption: Business Intelligence - Advisory Report Business Analytics - Alteryx Data Science - Decision Tree Foundational Data Management: Data Quality Management - Tool Evaluation Master & Reference Data Management - Advisory Report Meta Data Management - Artefacts Data Optimization: Query Optimization (Data Warehouse … quality management, metadata management, and master data management. Proficient in query optimization and data warehouse management. Experience with modern data science techniques, including decision trees and machine learning operations (ML Ops). Ability to evaluate and recommend tools for data quality management. Familiarity with real-time data integration more »

driven business transformation journey Develop tools for monitoring and analysing model performance and data precision. Present model findings and offer recommendations to key decision-makers and stakeholders The candidate: MSc/PhD in Data Science, Computer Science, Financial Engineering, Statistics, or related fields. 5+ years of industry experience … including distributions, statistical testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior more »

driven business transformation journey Develop tools for monitoring and analysing model performance and data precision. Present model findings and offer recommendations to key decision-makers and stakeholders The candidate: MSc/PhD in Data Science, Computer Science, Financial Engineering, Statistics, or related fields. 5+ years of industry experience … including distributions, statistical testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior more »

of contract damage recharge notifications, ensuring accuracy & facilitating revenue generation Action customer requests for end of contract collection of assets, utilising decision tree tool to ensure correct allocation of assets to remarketing channels Day-to-day management of logistic suppliers Producing sales quotations, subsequent paperwork, and any more »

live environments. Provide insights into current and future pricing performance using MI and modelling results. Coordinate pricing decisions and implementation across teams and decision-making bodies. Inform and influence senior management and heads of departments. Qualifications: Degree in a numerical discipline or equivalent. Experience in insurance pricing or … related analytical background. Proficiency in programming languages such as SAS, R, Matlab, or Python. Experience with predictive modelling techniques like Logistic Regression, Decision Trees, Random Forests, etc. Familiarity with Emblem and Radar. Strong communication skills to convey statistical concepts to non-statistical audiences. Self-motivated with excellent planning more »