9 of 9 XGBoost Jobs in the South East

will have the following skills and experience: Strong Python and SQL experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure, AWS, or GCP Benefits ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with ...

should be genuinely strong across most of them and honest about where you want to grow. Supervised & Ensemble Methods. Gradient-boosted trees (XGBoost, LightGBM, CatBoost) for tabular forecasting; understanding of when tree-based models outperform neural approaches on structured data, and vice versa. Strong intuition for regularisation, hyperparameter tuning ...

group with strong influence across risk, product, and strategy. The Role Lead credit decisioning strategy and model development. Stay hands on with modelling using XGBoost, GBM and related techniques. Oversee end-to-end model lifecycle from design to monitoring. Partner with risk, product, and engineering on decisioning and portfolio performance. ...

models across the customer lifecycle. THE ROLE The team builds and maintains all credit scoring and decisioning models using techniques such as GBM and XGBoost, owning the end-to-end model lifecycle from development through to monitoring and optimisation. Lead and develop a high-performing modelling team Remain hands ...