6 of 6 XGBoost Jobs in the Thames Valley

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 ...

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 ...

modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when to use a simple linear model and when to deploy … Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such as spending volatility or income stability—that predict affordability, repayment ...