1 to 25 of 52 XGBoost Jobs in the UK

Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning ANN, CNN, RNN, LSTM Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AINLTK, CBoW ...

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 ...

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 ...

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 ...