7 of 7 XGBoost Jobs in London

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 ...

understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community ...

team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data ...

learning and predictive modelling projects Advanced Python and SQL skills Experience working with large and complex datasets Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models Experience working in cloud-based environments, ideally Azure Strong stakeholder management and communication skills Ability to translate business challenges into analytical ...

Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches. Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams. ...

projects Requirements: Recent graduates or final year students. Should desirably have knowledge of Artificial Intelligence modeling techniques (logit, GLM, time series, random forests, clustering, XGBoost), statistical programming languages (SAS, R, Python, Matlab), big data tools and platforms (Hadoop, Hive, etc.) and cloud platforms (AWS, Azure, GCP). Solid academic record. ...

identify gaps between predicted vs. actual claim costs Working with large, messy insurance datasets across multiple product lines Tools & tech: Python, SQL, AzureML, XGBoost Opportunity to mentor within the team ...