8 of 8 XGBoost Jobs in London

expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

Understanding of object-oriented development principles and software engineering best practices Knowledge of machine learning concepts and frameworks including: PyTorch Scikit-Learn NumPy Pandas XGBoost NLTK SQL skills with the ability to query and manipulate structured datasets Understanding of REST APIs and API integration Familiarity with Large Language Models (LLMs ...

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 ...

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 ...

Deep expertise with AWS SageMaker (training, processing, pipelines, endpoints, registry) and complementary AWS services. Expert‐level Python and ML Model frameworks (e.g. PyTorch, TensorFlow, XGBoost). Strong thought leadership in MLOps automation, CI/CD for ML, and model lifecycle management. Advanced experience designing explainability systems, reason codes, and governance ...

problems and solutions to technically guide more junior data scientists.· Expert in applied machine learning, including the techniques currently being used in PRISM (XGBoost and SHAP)· Experience of using machine learning to solve commercial predictive· Ideally, experience with Causal MLBoth roles require Stakeholder management skills (defining and prioritising requirements, contributing ...

problems and solutions to technically guide more junior data scientists.· Expert in applied machine learning, including the techniques currently being used in PRISM (XGBoost and SHAP)· Experience of using machine learning to solve commercial predictive· Ideally, experience with Causal MLBoth roles require Stakeholder management skills (defining and prioritising requirements, contributing ...

Tripledot Studios is one of the largest independent mobile games companies in the world. We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios. Our expanded portfolio includes ...