1 to 25 of 41 XGBoost Jobs in the UK excluding London

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data ...

Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Strong data analysis, statistical modelling, and experimentation skills. Experience with data visualisation tools and techniques. Proficiency in programming languages such as Python ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...

random forests, gradient boosting) for structured and semi-structured data. Perform feature engineering, model selection, hyperparameter tuning, and evaluation using tools like scikit-learn, XGBoost, LightGBM. Build robust data preprocessing pipelines and scalable workflows for model training and inference. Collaborate on the development of agentic AI components — systems capable ...