5 of 5 Remote/Hybrid XGBoost Jobs in the UK

developing and deploying credit risk models, including: Probability of Default (PD) models Scorecards Risk segmentation models Experience evaluating and implementing challenger models such as XGBoost while balancing explainability and regulatory requirements. Strong understanding of model performance metrics including AUC, Gini, KS, calibration, and business impact measurement. Experience deploying production-ready ...

have a general understanding of REST APIs (design, integration, authentication). You have experience building, tuning, or deploying ML models (e.g., scikit‐learn, XGBoost, PyTorch, TensorFlow) in production settings. Experience with AI use cases in financial services (e.g. fraud detection, credit scoring, underwriting) is a strong plus. You are comfortable ...

Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you’ll bring Hands ...

track record of handling large-scale, high-granularity sports datasets and feeds. ● Predictive Modeling: Deep proficiency with the PyData stack (pandas, numpy, scikit-learn, XGBoost) and advanced machine learning methods including neural networks and random forests. ● Analytical Domain Knowledge: A professional-level understanding of cricket match dynamics and the factors ...

deal scoring (classification, regression, ranking) Analyse financial, credit, and time-series data to extract predictive signals Build and benchmark models such as: Gradient boosting (XGBoost, LightGBM, CatBoost) Random Forests Logistic/linear regression Design LLM-powered workflows for: Document understanding (loan docs, credit memos, financials) Risk factor extraction Deal-level … Regression, classification, and ranking models Time-series analysis & feature engineering Hands-on experience with: Python (pandas, NumPy, scikit-learn, etc.) Gradient boosting frameworks (XGBoost/LightGBM/CatBoost) Experience working with LLMs (prompting, RAG, embeddings, evaluation) Ability to work across structured + unstructured data Strong communication skills – able to engage ...