5 of 5 Remote/Hybrid Decision Tree Jobs in the UK

platform, workspaces, and cabinet structures. Legal Tech & Workflow Logic: Strong background in legal technology, document assembly, and translating complex legal processes into structured decision trees. Problem-Solving Skills: Ability to quickly step into existing systems, audit workflows, and keep projects moving independently. Communication: Excellent stakeholder management skills ...

platform, workspaces, and cabinet structures. Legal Tech & Workflow Logic: Strong background in legal technology, document assembly, and translating complex legal processes into structured decision trees. Problem-Solving Skills: Ability to quickly step into existing systems, audit workflows, and keep projects moving independently. Communication: Excellent stakeholder management skills ...

models they chose, the trade-offs, and how they measured success in production Key responsibilities Design, build and validate classical ML models (e.g. regression, tree-based ensembles, clustering) to solve real business problems Select appropriate algorithms and clearly justify model choices to technical and non-technical stakeholders Develop clean … take models from prototype to production Essential skills & experience Classical/traditional ML: Proven experience with models such as linear and logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM), SVMs and clustering. You can explain which models you've used, why you chose them and what ...

models they chose, the trade-offs, and how they measured success in production Key responsibilities Design, build and validate classical ML models (e.g. regression, tree-based ensembles, clustering) to solve real business problems Select appropriate algorithms and clearly justify model choices to technical and non-technical stakeholders Develop clean … take models from prototype to production Essential skills & experience Classical/traditional ML: Proven experience with models such as linear and logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM), SVMs and clustering. You can explain which models you've used, why you chose them and what ...

recommender systems use cases in our games. The work involves tabular machine learning, including neural networks and approaches such as gradient-boosted decision trees. You'll focus on understanding the data, developing features and improving the models, rather than primarily owning production deployment. You'll work toward defined … XGBoost, CatBoost or scikit-learn could all be relevant; no single framework is required. Experience designing features and labels, choosing metrics for the decision a model makes and judging when offline results warrant an A/B test. Proficiency in SQL and the ability to write efficient queries ...